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abortExperiment() - Method in class weka.experiment.RemoteExperiment: Set the abort flag
ABS - Static variable in interface weka.core.mathematicalexpression.sym
ABS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
AbstractAssociator - Class in weka.associations: Abstract scheme for learning associations.
AbstractAssociator() - Constructor for class weka.associations.AbstractAssociator
AbstractClassifier - Class in weka.classifiers: Abstract classifier.
AbstractClassifier() - Constructor for class weka.classifiers.AbstractClassifier
AbstractClusterer - Class in weka.clusterers: Abstract clusterer.
AbstractClusterer() - Constructor for class weka.clusterers.AbstractClusterer
AbstractDataSink - Class in weka.gui.beans: Abstract class for objects that store instances to some destination.
AbstractDataSink() - Constructor for class weka.gui.beans.AbstractDataSink
AbstractDataSinkBeanInfo - Class in weka.gui.beans: Bean info class for the AbstractDataSink
AbstractDataSinkBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSinkBeanInfo
AbstractDataSource - Class in weka.gui.beans: Abstract class for objects that can provide instances from some source
AbstractDataSource() - Constructor for class weka.gui.beans.AbstractDataSource: Creates a new AbstractDataSource instance.
AbstractDataSourceBeanInfo - Class in weka.gui.beans: Bean info class for AbstractDataSource.
AbstractDataSourceBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo
AbstractDensityBasedClusterer - Class in weka.clusterers: Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
AbstractDensityBasedClusterer() - Constructor for class weka.clusterers.AbstractDensityBasedClusterer
AbstractEvaluationMetric - Class in weka.classifiers.evaluation: Abstract base class for pluggable classification/regression evaluation metrics.
AbstractEvaluationMetric() - Constructor for class weka.classifiers.evaluation.AbstractEvaluationMetric
AbstractEvaluationMetric.UnknownStatisticException - Exception in weka.classifiers.evaluation: Exception for subclasses to throw if asked for a statistic that is not part of their implementation
AbstractEvaluationMetric.UnknownStatisticException(String) - Constructor for exception weka.classifiers.evaluation.AbstractEvaluationMetric.UnknownStatisticException: Constructs a new UnknownStatisticsException
AbstractEvaluator - Class in weka.gui.beans: Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
AbstractEvaluator() - Constructor for class weka.gui.beans.AbstractEvaluator: Constructor
AbstractFileLoader - Class in weka.core.converters: Abstract superclass for all file loaders.
AbstractFileLoader() - Constructor for class weka.core.converters.AbstractFileLoader
AbstractFileSaver - Class in weka.core.converters: Abstract class for Savers that save to a file Valid options are: -i input arff file
The input filw in arff format.
AbstractFileSaver() - Constructor for class weka.core.converters.AbstractFileSaver
AbstractInstance - Class in weka.core: Abstract class providing common functionality for the original instance implementations.
AbstractInstance() - Constructor for class weka.core.AbstractInstance
AbstractLoader - Class in weka.core.converters: Abstract class gives default implementation of setSource methods.
AbstractLoader() - Constructor for class weka.core.converters.AbstractLoader
AbstractOffscreenChartRenderer - Class in weka.gui.beans: Abstract base class for offscreen chart renderers.
AbstractOffscreenChartRenderer() - Constructor for class weka.gui.beans.AbstractOffscreenChartRenderer
AbstractOutput - Class in weka.classifiers.evaluation.output.prediction: A superclass for outputting the classifications of a classifier.
AbstractOutput() - Constructor for class weka.classifiers.evaluation.output.prediction.AbstractOutput: Initializes the output class.
AbstractPlotInstances - Class in weka.gui.explorer: Abstract superclass for generating plottable instances.
AbstractPlotInstances() - Constructor for class weka.gui.explorer.AbstractPlotInstances: Initializes the container.
AbstractPMMLProducerHelper - Class in weka.classifiers.pmml.producer: Abstract base class for PMMLProducer helper classes to extend.
AbstractPMMLProducerHelper() - Constructor for class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper
AbstractSaver - Class in weka.core.converters: Abstract class for Saver
AbstractSaver() - Constructor for class weka.core.converters.AbstractSaver
AbstractTestSetProducer - Class in weka.gui.beans: Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTestSetProducer() - Constructor for class weka.gui.beans.AbstractTestSetProducer: Creates a new AbstractTestSetProducer instance.
AbstractTestSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTestSetProducer
AbstractTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo
AbstractTimeSeries - Class in weka.filters.unsupervised.attribute: An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeries() - Constructor for class weka.filters.unsupervised.attribute.AbstractTimeSeries
AbstractTrainAndTestSetProducer - Class in weka.gui.beans: Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTrainAndTestSetProducer() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducer: Creates a new AbstractTrainAndTestSetProducer instance.
AbstractTrainAndTestSetProducerBeanInfo - Class in weka.gui.beans: Bean info class for AbstractTrainAndTestSetProducers
AbstractTrainAndTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
AbstractTrainingSetProducer - Class in weka.gui.beans: Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
AbstractTrainingSetProducer() - Constructor for class weka.gui.beans.AbstractTrainingSetProducer: Creates a new AbstractTrainingSetProducer instance.
AbstractTrainingSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTrainingSetProducer
AbstractTrainingSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
accept(File) - Method in class weka.core.ClassCache.ClassFileFilter: Checks whether the file is a class.
accept(File) - Method in class weka.core.ClassCache.DirectoryFilter: Checks whether the file is a directory.
accept(File) - Method in class weka.gui.ExtensionFileFilter: Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
accept(File, String) - Method in class weka.gui.ExtensionFileFilter: Returns true if the file in the given directory with the given name should be accepted.
ACCEPT - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: States that the user has accepted the tree.
acceptAssociationRules(BatchAssociationRulesEvent) - Method in interface weka.gui.beans.BatchAssociationRulesListener: Accept a BatchAssociationRulesEvent
acceptClassifier(BatchClassifierEvent) - Method in interface weka.gui.beans.BatchClassifierListener: Accept a BatchClassifierEvent
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Accept a classifier to be evaluated.
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Accepts and processes a classifier encapsulated in an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in interface weka.gui.beans.IncrementalClassifierListener: Accept the event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process an incremental classifier event
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save an incrementally trained classifier.
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained classifier.
acceptClusterer(BatchClustererEvent) - Method in interface weka.gui.beans.BatchClustererListener: Accept a BatchClustererEvent
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Accept a clusterer to be evaluated
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch clusterer event
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained clusterer.
acceptConfiguration(ConfigurationEvent) - Method in interface weka.gui.beans.ConfigurationListener: Implementers do not have to do anything in this method (see the above documentation).
acceptDataPoint(ChartEvent) - Method in interface weka.gui.beans.ChartListener
acceptDataPoint(ChartEvent) - Method in class weka.gui.beans.StripChart: Accept a data point (encapsulated in a chart event) to plot
acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart: Accept a data point to plot
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a threshold data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Subclass must implement
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Associator
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassValuePicker
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.CostBenefitAnalysis: Accept a threshold data event and set up the visualization.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in interface weka.gui.beans.DataSourceListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Filter: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Join: Accept and process a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a threshold curve.
acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a scheme error plot.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a dataset event and starts the writing process in batch mode
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.Saver: Method reacts to a threshold data event ans starts the writing process in batch mode.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TestSetMaker: Accepts and processes a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a data set for displaying as text
acceptDataSet(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainingSetMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a data set
acceptDataSet(VisualizableErrorEvent) - Method in interface weka.gui.beans.VisualizableErrorListener
acceptGraph(GraphEvent) - Method in interface weka.gui.beans.GraphListener: Describe acceptGraph method here.
acceptGraph(GraphEvent) - Method in class weka.gui.beans.GraphViewer: Accept a graph
acceptImage(ImageEvent) - Method in interface weka.gui.beans.ImageListener: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageSaver: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageViewer
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept an instance
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Appender: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.ClassAssigner
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Classifier: Accepts an instance for incremental processing.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Filter: Accept an instance for processing by StreamableFilters only
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.FlowByExpression
acceptInstance(InstanceEvent) - Method in interface weka.gui.beans.InstanceListener: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Accept an instance to add to the batch.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Join
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Saver: Methods reacts to instance events and saves instances incrementally.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Sorter: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringReplacer: Accept and process an instance event
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.AveragingResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.CSVResultListener: Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultListener: Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.InstancesResultListener: Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.LearningRateResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in interface weka.experiment.ResultListener: Accepts results from a ResultProducer.
acceptsInstances() - Method in class weka.gui.beans.AttributeSummarizer: Returns true if this perspective accepts instances
acceptsInstances() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
acceptsInstances() - Method in class weka.gui.beans.ScatterPlotMatrix: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.SQLViewerPerspective: Returns true if this perspective accepts instances
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a test set for a batch trained classifier
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a test set for a batch trained clusterer
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Filter: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Join: Accept and process a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a test set event and starts the writing process in batch mode
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in interface weka.gui.beans.TestSetListener: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a test set for displaying as text
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainingSetMaker
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener: Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.TextSaver: Accept and process an TextEvent
acceptText(TextEvent) - Method in class weka.gui.beans.TextViewer: Accept some text
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Associator: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a training set and builds batch classifier
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a training set and builds batch clusterer
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Filter: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Join: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a training set event and starts the writing process in batch mode
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TestSetMaker
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a training set
actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the actual entropy
action_table() - Method in class weka.core.json.Parser: Access to parse-action table.
action_table() - Method in class weka.core.mathematicalexpression.Parser: Access to parse-action table.
action_table() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser: Access to parse-action table.
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.AlgorithmListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.DatasetListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.HostListPanel: Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.RunPanel: Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class weka.gui.SimpleCLIPanel: Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent) - Method in class weka.gui.streams.InstanceLoader
actionPerformed(ActionEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs the action associated with the ActionEvent.
ACTIVATIONFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for ACTIVATION-FUNCTION.
ActiveHNode - Class in weka.classifiers.trees.ht: Node that is "active" (i.e.
ActiveHNode() - Constructor for class weka.classifiers.trees.ht.ActiveHNode
actual() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the actual class value.
actual() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the actual class value.
actual() - Method in interface weka.classifiers.evaluation.Prediction: Gets the actual class value.
actualNumBags() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of non-empty bags of distribution.
actualNumClasses() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in distribution.
actualNumClasses(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in given bag.
acuityTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
AdaBoostM1 - Class in weka.classifiers.meta: Class for boosting a nominal class classifier using the Adaboost M1 method.
AdaBoostM1() - Constructor for class weka.classifiers.meta.AdaBoostM1: Constructor.
add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to given bag.
add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds counts to given bag.
add(AlgVector) - Method in class weka.core.AlgVector: Returns the sum of this vector with another.
add(String) - Method in class weka.core.ClassCache: Adds the classname to the cache.
add(Instance) - Method in class weka.core.Instances: Adds one instance to the end of the set.
add(int, Instance) - Method in class weka.core.Instances: Adds one instance at the given position in the list.
add(Matrix) - Method in class weka.core.Matrix: Deprecated. Returns the sum of this matrix with another.
add(String) - Method in class weka.core.Stopwords: adds the given word to the stopword list (is automatically converted to lower case and trimmed)
add(TechnicalInformation) - Method in class weka.core.TechnicalInformation: adds the given information to the list of additional technical informations
add(TechnicalInformation.Type) - Method in class weka.core.TechnicalInformation: Adds an empty technical information with the given type to the list of additional informations and returns the instance.
add(PrintStream) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO timestamp and NO prefix.
add(PrintStream, boolean) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO prefix.
add(PrintStream, boolean, String) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams.
add(String) - Method in class weka.core.Trie: Ensures that this collection contains the specified element.
add(String) - Method in class weka.core.Trie.TrieNode: adds the given string to its children (creates children if necessary)
add(String, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the property with the given displayname to its internal list.
add(Class<?>, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the given class to its internal list.
add(double, double) - Method in class weka.experiment.PairedStats: Add an observed pair of values.
add(double[], double[]) - Method in class weka.experiment.PairedStats: Adds an array of observed pair of values.
add(double) - Method in class weka.experiment.Stats: Adds a value to the observed values
add(double, double) - Method in class weka.experiment.Stats: Adds a value that has been seen n times to the observed values
Add - Class in weka.filters.unsupervised.attribute: An instance filter that adds a new attribute to the dataset.
Add() - Constructor for class weka.filters.unsupervised.attribute.Add
add(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Inserts the specified element at the specified position in this list.
add(Object) - Method in class weka.gui.GenericObjectEditorHistory: Adds the object to the history.
add(String) - Method in class weka.gui.HierarchyPropertyParser: Add the given item of property to the tree
ADD_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
addActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Register a listener to be notified when plotting completes
addActionListener(ActionListener) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Add a listener interested in kowing about editor status changes
addActionListener(ActionListener) - Method in class weka.gui.visualize.ClassPanel: Add an action listener that will be notified if the user changes the colour of a label
addActionListener(ActionListener) - Method in class weka.gui.visualize.VisualizePanel: Add a listener for this visualize panel
addAll(Collection<? extends T>) - Method in class weka.core.neighboursearch.covertrees.Stack: Adds all the given elements in the stack.
addAll(Collection<? extends String>) - Method in class weka.core.Trie: Adds all of the elements in the specified collection to this collection
addAllBeansToContainer(JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance: Adds all beans to the supplied component
addAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given property (display name) to the list of allowed properties for the specified class.
addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats: Add a rule to the ruleset and update the stats
addArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(String, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between parent node and each of the nodes in a given list.
addArray(String) - Method in class weka.core.json.JSONNode: Adds an array child to the object.
addArrayElement(Object) - Method in class weka.core.json.JSONNode: Adds an array element child to the array.
addAssociationModelOrBaselineModelOrClusteringModes(Object) - Method in class weka.core.pmml.jaxbbindings.PMML
addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel: Add a listener to the list of things listening to this panel
addAttributeSpec(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Add an attribute spec to the list
addBatchAssociationRulesListener(BatchAssociationRulesListener) - Method in class weka.gui.beans.Associator: Add a batch association rules listener
addBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier: Add a batch classifier listener
addBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer: Add a batch clusterer listener
addBean(JComponent, Integer...) - Method in class weka.gui.beans.BeanInstance: Adds this bean to the global list of beans and to the supplied container.
addBeanInstances(Vector<Object>, JComponent) - Static method in class weka.gui.beans.BeanInstance: Adds the supplied collection of beans to the end of the list of collections and to the JComponent container (if not null)
addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the cancel button.
addCapabilities(String, Capabilities) - Static method in class weka.gui.PropertySheetPanel: generates a string from the capapbilities, suitable to add to the help text.
addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer: adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel: Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable: Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel: Enable objects to listen for changes to the check box
addChild(Edge) - Method in class weka.gui.treevisualizer.Node: Set the value of children.
addChildClique(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
addChildFrame(Container) - Method in class weka.gui.GUIChooser: adds the given child frame to the list of frames.
addChildFrame(Container) - Method in class weka.gui.Main: adds the given child frame to the list of frames.
AddClassification - Class in weka.filters.supervised.attribute: A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
AddClassification() - Constructor for class weka.filters.supervised.attribute.AddClassification
AddCluster - Class in weka.filters.unsupervised.attribute: A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
Either the clustering algorithm gets built with the first batch of data or one specifies are serialized clusterer model file to use instead.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addConnections(Vector<BeanConnection>) - Static method in class weka.gui.beans.BeanConnection: Add the supplied collection of connections to the end of the list.
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.RegressionModel
addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection: Adds a scheme parameter to the list of parameters to be set by cross-validation
addDataDictionary(Instances, PMML) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Adds a data dictionary to the supplied PMML object.
addDataField(DataField) - Method in class weka.core.pmml.jaxbbindings.DataDictionary
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Appender: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.FlowByExpression
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Join: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Sorter: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringLabeler: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringReplacer: Add a data source listener
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.LocalTransformations
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary
addElement(E) - Method in class weka.core.FastVector: Deprecated. Adds an element to this vector.
addElement(int, int, double) - Method in class weka.core.Matrix: Deprecated. Add a value to an element.
addElement(double) - Method in class weka.core.matrix.DoubleVector: Adds an element into the vector
addElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Adds the specified component to the end of this list.
addEmptyRow() - Method in class weka.gui.beans.InteractiveTableModel: Adds an empty row to the model
addErrs(double, double, float) - Static method in class weka.classifiers.trees.j48.Stats: Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
AddExpression - Class in weka.filters.unsupervised.attribute: An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
AddExpression() - Constructor for class weka.filters.unsupervised.attribute.AddExpression
addFile(String) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFile(File) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFileFilter(FileFilter) - Method in class weka.gui.beans.FileEnvironmentField: Add a file filter to use
addFromProperties(File) - Static method in class weka.gui.beans.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(InputStream) - Static method in class weka.gui.beans.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(Properties) - Static method in class weka.gui.beans.PluginManager: Add all key value pairs from the supplied properties object
addGraphListener(GraphListener) - Method in class weka.gui.beans.Associator: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer: Add a graph listener
addHeader(String, String) - Method in class weka.experiment.ResultMatrix: adds the key-value pair to the header.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
AddID - Class in weka.filters.unsupervised.attribute: An instance filter that adds an ID attribute to the dataset.
AddID() - Constructor for class weka.filters.unsupervised.attribute.AddID
addIgnored(String) - Method in class weka.core.xml.PropertyHandler: adds the given display name of a property to the ignore list.
addIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given class with the display name of a property to the ignore list.
addImageListener(ImageListener) - Method in class weka.gui.beans.DataVisualizer: Add an image listener
addImageListener(ImageListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add an image listener
addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier: Add an incremental classifier listener
addInstance(Instance) - Method in class weka.clusterers.Cobweb: Deprecated. updateClusterer(Instance) should be used instead
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Adds an instance to the tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Adds an instance to the ball tree.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.BallTree: Adds the given instance's info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.CoverTree: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.KDTree: Adds one instance to KDTree loosly.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Adds information from the given instance without modifying the datastructure a lot.
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Appender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
addInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.FlowByExpression
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Join: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Sorter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringLabeler: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringReplacer: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
addInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
addInstanceNumberAttribute() - Method in class weka.gui.visualize.PlotData2D: Adds an instance number attribute to the plottable instances,
addInstWithUnknown(Instances, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
additional() - Method in class weka.core.TechnicalInformation: returns an enumeration of all the additional technical informations (if there are any)
AdditionalMeasureProducer - Interface in weka.core: Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression - Class in weka.classifiers.meta: Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression() - Constructor for class weka.classifiers.meta.AdditiveRegression: Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier) - Constructor for class weka.classifiers.meta.AdditiveRegression: Constructor which takes base classifier as argument.
addKeyword(String, MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates a keyword with a particular formatting style.
addKeywords(String[], MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates the keywords with a particular formatting style.
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Method to add a LayoutCompleteEventListener
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method adds a LayoutCompleteEventListener to the LayoutEngine.
addMiningFields(MiningField) - Method in class weka.core.pmml.jaxbbindings.MiningSchema
addModel(SimpleLinearRegression) - Method in class weka.classifiers.functions.SimpleLinearRegression: Takes the given simple linear regression model and adds it to this one.
addModel(SimpleLinearRegression) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Takes the given simple linear regression model and adds it to this one.
addMouseListener(MouseListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a mouse listener.
addMouseListenerToHeader(JTable) - Method in class weka.gui.SortedTableModel: Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
addNode(String, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add new node to the network, initializing instances, parentsets, distributions.
addNode(String, int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node to network at a given position, initializing instances, parentsets, distributions.
addNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node value to a node.
AddNoise - Class in weka.filters.unsupervised.attribute: An instance filter that changes a percentage of a given attributes values.
AddNoise() - Constructor for class weka.filters.unsupervised.attribute.AddNoise
addNoise(Instances, int, int, int, boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise: add noise to the dataset a given percentage of the instances are changed in the way, that a set of instances are randomly selected using seed.
addNull(String) - Method in class weka.core.json.JSONNode: Adds a "null" child to the object.
addNullArrayElement() - Method in class weka.core.json.JSONNode: Adds a null array element child to the array.
addNumericPredictor(NumericPredictor) - Method in class weka.core.pmml.jaxbbindings.RegressionTable
addObject(String) - Method in class weka.core.json.JSONNode: Adds an object child to the object.
addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel: Adds an object to the results list
addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the ok button.
addOutputField(OutputField) - Method in class weka.core.pmml.jaxbbindings.Output
addParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set and update internals (specifically the cardinality of the parent set)
addParent(int, int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
addPCell(PCell) - Method in class weka.core.pmml.jaxbbindings.ParamMatrix
addPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D: Add a plot to the list of plots to display
addPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel: Set a new plot to the visualize panel
addPlugin(String, String, String) - Static method in class weka.gui.beans.PluginManager: Add a plugin.
addPreBuiltClassifier(Classifier) - Method in class weka.classifiers.meta.Vote: Add a prebuilt classifier to the list for use in the ensemble
addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a prediction in the confusion matrix.
addPredictions(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a whole bunch of predictions in the confusion matrix.
addPrimitive(String, Boolean) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Integer) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Double) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, String) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual: Add a listener for property change events
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.EnvironmentField
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor: Adds an object to the list of those that wish to be informed when the cost matrix changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel: Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor: Adds an object to the list of those that wish to be informed when the date format changes.
addPropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
addPSFontReplacement(String, String) - Static method in class weka.gui.visualize.PostscriptGraphics: adds the PS font name to replace and its replacement in the replacement hashtable
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances in given range to given bag.
addRelation(Instances) - Method in class weka.core.Attribute: Adds a relation to a relation-valued attribute.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.experiment.RemoteExperiment: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String) - Method in class weka.experiment.RemoteExperiment: Add a host name to the list of remote hosts
addRenderingHints(Map<?, ?>) - Method in class weka.gui.visualize.PostscriptGraphics
addRepaintNotify(Component) - Method in class weka.gui.visualize.ClassPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component) - Method in class weka.gui.visualize.LegendPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
addResult(String, StringBuffer) - Method in class weka.gui.ResultHistoryPanel: Adds a new result to the result list.
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel: adds the given listener to the list of listeners
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script: Adds the given listener to its internal list.
addStartupListener(StartUpListener) - Static method in class weka.gui.beans.KnowledgeFlowApp: Add a listener to be notified when startup is complete
addStartupListener(StartUpListener) - Static method in class weka.gui.Main: Add a listener to be notified when startup is complete.
addStringValue(String) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(Attribute, int) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addTab(String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel: adds a listener to the list that is notified each time a change to data model occurs.
addTarget(Target) - Method in class weka.core.pmml.jaxbbindings.Targets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer: Add a listener for test sets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a test set listener
addTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer: Add a listener for test set events
addTextListener(TextListener) - Method in class weka.gui.beans.Associator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Classifier: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Clusterer: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.TextViewer: Add a text listener
addThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a threshold data listener
addTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel: Adds the listener to the internal list.
addToDisabledList(List<String>) - Static method in class weka.gui.beans.PluginManager: Add the supplied list of fully qualified class names to the disabled list
addToDisabledList(String) - Static method in class weka.gui.beans.PluginManager: Add the supplied fully qualified class name to the list of disabled plugins
addToHistory() - Method in class weka.gui.PropertyPanel: Adds the current editor value to the history.
addToHistory(Object) - Method in class weka.gui.PropertyPanel: Adds the specified value to the history.
addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2: adds an element (Link) to the list.
addToPluginBeanProps(File) - Static method in class weka.gui.beans.BeansProperties
addToPluginBeanProps(File) - Static method in class weka.gui.beans.KnowledgeFlowApp
addTrainingInstance(Instance) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to the visualization dataset.
addTrainingInstanceFromMouseLocation(int, int, int, double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to our dataset, based on the coordinates of the mouse on the panel.
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer: Add a training set listener
addUndoPoint() - Method in interface weka.core.Undoable: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffPanel: adds the current state of the instances to the undolist
addUndoPoint() - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableModel: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class weka.gui.explorer.PreprocessPanel: Backs up the current state of the dataset, so the changes can be undone.
addURL(URL) - Static method in class weka.core.ClassloaderUtil: Add URL to CLASSPATH
AddUserFields - Class in weka.filters.unsupervised.attribute: A filter that adds new attributes with user specified type and constant value.
AddUserFields() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields: Constructs a new AddUserFields
AddUserFields.AttributeSpec - Class in weka.filters.unsupervised.attribute: Inner class encapsulating a new user-specified attribute to create.
AddUserFields.AttributeSpec() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Default constructor
AddUserFields.AttributeSpec(String) - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Constructor that takes an attribute specification in internal format
AddUserFieldsBeanInfo - Class in weka.filters.unsupervised.attribute: Bean info class for the AddUserFields filter.
AddUserFieldsBeanInfo() - Constructor for class weka.filters.unsupervised.attribute.AddUserFieldsBeanInfo
AddUserFieldsCustomizer - Class in weka.gui.filters: Customizer for the AddUserFields filter.
AddUserFieldsCustomizer() - Constructor for class weka.gui.filters.AddUserFieldsCustomizer: Constructor
addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Add a new data value to the current estimator.
addValue(Value) - Method in class weka.core.pmml.jaxbbindings.DataField
addValue(double, double, double) - Method in interface weka.estimators.ConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.DiscreteEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DNConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.Estimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.IncrementalEstimator: Add one value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.KernelEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.MahalanobisEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NNConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.NormalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.PoissonEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateDensityEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateIntervalEstimator: Adds a value to the interval estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateKernelEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateNormalEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateQuantileEstimator: Adds a value to the interval estimator.
addValues(Instances, int) - Method in class weka.estimators.Estimator: Initialize the estimator with a new dataset.
addValues(Instances, int, double, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator with all values of one attribute of a dataset.
addValues(Instances, int, int, int) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instance of one class.
addValues(Instances, int, int, int, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instance of one class.
AddValues - Class in weka.filters.unsupervised.attribute: Adds the labels from the given list to an attribute if they are missing.
AddValues() - Constructor for class weka.filters.unsupervised.attribute.AddValues
addVariable(String, String) - Method in class weka.core.Environment: Add a variable to the internal map of this properties object.
addVariableSystemWide(String, String) - Method in class weka.core.Environment: Add a a variable to the internal map of this properties object and to the global system-wide environment;
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.CostBenefitAnalysis
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer: Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to all bags weighting it according to given weights.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node: Will increase or decrease the postion of center.
adjustWeightsTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
ADNode - Class in weka.classifiers.bayes.net: The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
ADNode() - Constructor for class weka.classifiers.bayes.net.ADNode: Creates new ADNode
advanceCounters() - Method in class weka.experiment.Experiment: Increments iteration counters appropriately.
advanceCounters() - Method in class weka.experiment.RemoteExperiment: overides the one in Experiment
aggregate(Evaluation) - Method in class weka.classifiers.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(NaiveBayes) - Method in class weka.classifiers.bayes.NaiveBayes
aggregate(NaiveBayesMultinomialText) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
aggregate(Evaluation) - Method in class weka.classifiers.evaluation.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(Logistic) - Method in class weka.classifiers.functions.Logistic: Aggregate an object with this one
aggregate(SGD) - Method in class weka.classifiers.functions.SGD: Aggregate an object with this one
aggregate(SGDText) - Method in class weka.classifiers.functions.SGDText: Aggregate an object with this one
aggregate(Bagging) - Method in class weka.classifiers.meta.Bagging: Aggregate an object with this one
aggregate(Classifier) - Method in class weka.classifiers.meta.Vote: Aggregate an object with this one
aggregate(RandomForest) - Method in class weka.classifiers.trees.RandomForest
aggregate(E) - Method in interface weka.core.Aggregateable: Aggregate an object with this one
Aggregate - Class in weka.core.pmml.jaxbbindings: Java class for Aggregate element declaration.
Aggregate() - Constructor for class weka.core.pmml.jaxbbindings.Aggregate
aggregate(DiscreteEstimator) - Method in class weka.estimators.DiscreteEstimator
aggregate(KernelEstimator) - Method in class weka.estimators.KernelEstimator
aggregate(NormalEstimator) - Method in class weka.estimators.NormalEstimator
Aggregateable<E> - Interface in weka.core: Interface to something that can aggregate an object of the same type with itself.
AggregateableEvaluation - Class in weka.classifiers: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
AggregateableEvaluation - Class in weka.classifiers.evaluation: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
aggregateCanopies(List<Canopy>, double, double, NormalizableDistance, Filter, int) - Static method in class weka.clusterers.Canopy: Aggregate the canopies from a list of Canopy clusterers together into one final model.
Agrawal - Class in weka.datagenerators.classifiers.classification: Generates a people database and is based on the paper by Agrawal et al.:
R.
Agrawal() - Constructor for class weka.datagenerators.classifiers.classification.Agrawal: initializes the generator with default values
AIC - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
AlgorithmListPanel - Class in weka.gui.experiment: This panel controls setting a list of algorithms for an experiment to iterate over.
AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel: Creates the algorithm list panel with the given experiment.
AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel: Create the algorithm list panel initially disabled.
AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment: Class required to show the Classifiers nicely in the list
AlgorithmListPanel.ObjectCellRenderer() - Constructor for class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
AlgVector - Class in weka.core: Class for performing operations on an algebraic vector of floating-point values.
AlgVector(int) - Constructor for class weka.core.AlgVector: Constructs a vector and initializes it with default values.
AlgVector(double[]) - Constructor for class weka.core.AlgVector: Constructs a vector using a given array.
AlgVector(Instances, Random) - Constructor for class weka.core.AlgVector: Constructs a vector using a given data format.
AlgVector(Instance) - Constructor for class weka.core.AlgVector: Constructs a vector using an instance.
alignBottom(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the bottom most node in the list
alignLeft(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the left most node in the list
alignRight(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the right most node in the list
alignTop(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the top most node in the list
ALL - Static variable in class weka.core.Debug: the log level All
AllFilter - Class in weka.filters: A simple instance filter that passes all instances directly through.
AllFilter() - Constructor for class weka.filters.AllFilter
AllJavadoc - Class in weka.core: Applies all known Javadoc-derived classes to a source file.
AllJavadoc() - Constructor for class weka.core.AllJavadoc
allowAccessToFullInputFormat() - Method in class weka.filters.SimpleBatchFilter: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowAccessToFullInputFormat() - Method in class weka.filters.supervised.attribute.MergeNominalValues: We need access to the full input data in determineOutputFormat.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: We need access to the full input data in determineOutputFormat.
allowed() - Method in class weka.core.xml.PropertyHandler: returns an enumeration of the classnames for which only certain properties (display names) are allowed
allowUnclassifiedInstancesTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
AlphabeticTokenizer - Class in weka.core.tokenizers: Alphabetic string tokenizer, tokens are to be formed only from contiguous alphabetic sequences.
AlphabeticTokenizer() - Constructor for class weka.core.tokenizers.AlphabeticTokenizer
alphaTipText() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
Alternate - Class in weka.core.pmml.jaxbbindings: Java class for Alternate element declaration.
Alternate() - Constructor for class weka.core.pmml.jaxbbindings.Alternate
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the tip text for this property
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
and(Capabilities) - Method in class weka.core.Capabilities: performs an AND conjunction with the capabilities of the given Capabilities object and updates itself
AND - Static variable in interface weka.core.mathematicalexpression.sym
AND - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
Annotation - Class in weka.core.pmml.jaxbbindings: Java class for Annotation element declaration.
Annotation() - Constructor for class weka.core.pmml.jaxbbindings.Annotation
Anova - Class in weka.core.pmml.jaxbbindings: Java class for Anova element declaration.
Anova() - Constructor for class weka.core.pmml.jaxbbindings.Anova
AnovaRow - Class in weka.core.pmml.jaxbbindings: Java class for AnovaRow element declaration.
AnovaRow() - Constructor for class weka.core.pmml.jaxbbindings.AnovaRow
AntecedentSequence - Class in weka.core.pmml.jaxbbindings: Java class for AntecedentSequence element declaration.
AntecedentSequence() - Constructor for class weka.core.pmml.jaxbbindings.AntecedentSequence
AnyDistribution - Class in weka.core.pmml.jaxbbindings: Java class for AnyDistribution element declaration.
AnyDistribution() - Constructor for class weka.core.pmml.jaxbbindings.AnyDistribution
append(String, String) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list (with the associated icon at the beginning)
append(Object) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list
appendBeans(JComponent, Vector<Object>, int) - Static method in class weka.gui.beans.BeanInstance
appendConnections(Vector<BeanConnection>, int) - Static method in class weka.gui.beans.BeanConnection: Append the supplied connections to the list for the given tab index
appendElements(Collection<? extends E>) - Method in class weka.core.FastVector: Deprecated. Appends all elements of the supplied vector to this vector.
Appender - Class in weka.gui.beans: A bean that appends multiple incoming data connections into a single data set.
Appender() - Constructor for class weka.gui.beans.Appender: Constructs a new Appender.
AppenderBeanInfo - Class in weka.gui.beans: Bean info class for the appender bean
AppenderBeanInfo() - Constructor for class weka.gui.beans.AppenderBeanInfo
appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender: Return a tip text suitable for displaying in a GUI
Application - Class in weka.core.pmml.jaxbbindings: Java class for Application element declaration.
Application() - Constructor for class weka.core.pmml.jaxbbindings.Application
Application(String, String) - Constructor for class weka.core.pmml.jaxbbindings.Application
appliesToNominalClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is nominal
appliesToNumericClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is numeric
Apply - Class in weka.core.pmml.jaxbbindings: Java class for Apply element declaration.
Apply() - Constructor for class weka.core.pmml.jaxbbindings.Apply
apply(Instance) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Apply this rule to the supplied instance
apply(Instance) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Apply this rule to the supplied instance
applyClassifier(PMMLModel, Instances) - Static method in class weka.core.pmml.PMMLFactory
applyCostMatrix(Instances, Random) - Method in class weka.classifiers.CostMatrix: Applies the cost matrix to a set of instances.
applyMinMaxRescaleCast(double) - Method in class weka.core.pmml.TargetMetaInfo: Apply min and max, rescaleFactor, rescaleConstant and castInteger - in that order (where defined).
applyMissingAndOutlierTreatments(double[]) - Method in class weka.core.pmml.MiningSchema: Apply both missing and outlier treatments to an incoming instance.
applyMissingValuesTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the missing value treatments (if any) to an incoming instance.
applyMissingValueTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the missing value treatment method for this field.
applyOutlierTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the outlier treatment method for this field.
applyOutlierTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the outlier treatment methods (if any) to an incoming instance.
applyRules(Instance) - Method in class weka.gui.beans.SubstringReplacerRules
APPROVE_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies an OK property selection.
APPROVE_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies an OK property selection
Apriori - Class in weka.associations: Class implementing an Apriori-type algorithm.
Apriori() - Constructor for class weka.associations.Apriori: Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
AprioriItemSet - Class in weka.associations: Class for storing a set of items.
AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet: Constructor
areaUnderPRC(int) - Method in class weka.classifiers.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderPRC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
ARFF_ATTRIBUTE - Static variable in class weka.core.Attribute: The keyword used to denote the start of an arff attribute declaration
ARFF_ATTRIBUTE_DATE - Static variable in class weka.core.Attribute: The keyword used to denote a date attribute
ARFF_ATTRIBUTE_INTEGER - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_NUMERIC - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_REAL - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_RELATIONAL - Static variable in class weka.core.Attribute: The keyword used to denote a relation-valued attribute
ARFF_ATTRIBUTE_STRING - Static variable in class weka.core.Attribute: The keyword used to denote a string attribute
ARFF_DATA - Static variable in class weka.core.Instances: The keyword used to denote the start of the arff data section
ARFF_END_SUBRELATION - Static variable in class weka.core.Attribute: The keyword used to denote the end of the declaration of a subrelation
ARFF_RELATION - Static variable in class weka.core.Instances: The keyword used to denote the start of an arff header
ArffLoader - Class in weka.core.converters: Reads a source that is in arff (attribute relation file format) format.
ArffLoader() - Constructor for class weka.core.converters.ArffLoader
ArffLoader.ArffReader - Class in weka.core.converters: Reads data from an ARFF file, either in incremental or batch mode.
ArffLoader.ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data completely from the reader.
ArffLoader.ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
ArffLoader.ArffReader(Reader, int, boolean) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads only the header and reserves the specified space for instances.
ArffLoader.ArffReader(Reader, Instances, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data without header according to the specified template.
ArffLoader.ArffReader(Reader, Instances, int, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffLoader.ArffReader(Reader, Instances, int, int, boolean, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffPanel - Class in weka.gui.arffviewer: A Panel representing an ARFF-Table and the associated filename.
ArffPanel() - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with no data
ArffPanel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel and loads the specified file
ArffPanel(Instances) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with the given data
ArffSaver - Class in weka.core.converters: Writes to a destination in arff text format.
ArffSaver() - Constructor for class weka.core.converters.ArffSaver: Constructor
ArffSortedTableModel - Class in weka.gui.arffviewer: A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
ArffSortedTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but loads the given file and creates from that a model
ArffSortedTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but uses the given data to create a model from that
ArffSortedTableModel(TableModel) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter with the given model
ArffTable - Class in weka.gui.arffviewer: A specialized JTable for the Arff-Viewer.
ArffTable() - Constructor for class weka.gui.arffviewer.ArffTable: initializes with no model
ArffTable(TableModel) - Constructor for class weka.gui.arffviewer.ArffTable: initializes with the given model
ArffTableCellRenderer - Class in weka.gui.arffviewer: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ArffTableCellRenderer() - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with a standard color
ArffTableCellRenderer(Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableCellRenderer(Color, Color, Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableModel - Class in weka.gui.arffviewer: The model for the Arff-Viewer.
ArffTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the object and loads the given file
ArffTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the model with the given data
ArffViewer - Class in weka.gui.arffviewer: A little tool for viewing ARFF files.
ArffViewer() - Constructor for class weka.gui.arffviewer.ArffViewer: initializes the object
ArffViewerMainPanel - Class in weka.gui.arffviewer: The main panel of the ArffViewer.
ArffViewerMainPanel(Container) - Constructor for class weka.gui.arffviewer.ArffViewerMainPanel: initializes the object
Array - Class in weka.core.pmml: Class for encapsulating a PMML Array element.
Array.ArrayType - Enum in weka.core.pmml
arrayLeftDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division, C = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division in place, A = A.\B
arrayRightDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division, C = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division in place, A = A./B
arrayTimes(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication, C = A.*B
arrayTimesEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication in place, A = A.*B
arrayToString(Object) - Static method in class weka.core.Utils: Returns the given Array in a string representation.
arrayToString(Object[]) - Static method in class weka.experiment.DatabaseUtils: Converts an array of objects to a string by inserting a space between each element.
ArrayType - Class in weka.core.pmml.jaxbbindings: Java class for ArrayType complex type.
ArrayType() - Constructor for class weka.core.pmml.jaxbbindings.ArrayType
ASEvaluation - Class in weka.attributeSelection: Abstract attribute selection evaluation class
ASEvaluation() - Constructor for class weka.attributeSelection.ASEvaluation
ASSearch - Class in weka.attributeSelection: Abstract attribute selection search class.
ASSearch() - Constructor for class weka.attributeSelection.ASSearch
assign(Capabilities) - Method in class weka.core.Capabilities: retrieves the data from the given Capabilities object
assign(TestInstances) - Method in class weka.core.TestInstances: updates itself with all the settings from the given TestInstances object
assign(Tester) - Method in class weka.experiment.PairedTTester: retrieves all the settings from the given Tester
assign(ResultMatrix) - Method in class weka.experiment.ResultMatrix: acquires the data from the given matrix.
assign(Tester) - Method in interface weka.experiment.Tester: retrieves all the settings from the given Tester
assignCanopies(Instance) - Method in class weka.clusterers.Canopy: Uses T1 distance to assign canopies to the supplied instance.
assignIDs(int) - Method in class weka.classifiers.trees.j48.ClassifierTree: Assigns a uniqe id to every node in the tree.
assignIDs(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns unique IDs to all nodes in the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns numbers to the logistic regression models at the leaves of the tree
assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class weka.core.neighboursearch.KDTree: Assigns instances of this node to center.
associatedConnections(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
AssociationModel - Class in weka.core.pmml.jaxbbindings: Java class for AssociationModel element declaration.
AssociationModel() - Constructor for class weka.core.pmml.jaxbbindings.AssociationModel
AssociationRule - Class in weka.associations: Abstract class for storing and manipulating an association rule.
AssociationRule() - Constructor for class weka.associations.AssociationRule
AssociationRule - Class in weka.core.pmml.jaxbbindings: Java class for AssociationRule element declaration.
AssociationRule() - Constructor for class weka.core.pmml.jaxbbindings.AssociationRule
AssociationRules - Class in weka.associations: Class encapsulating a list of association rules.
AssociationRules(List<AssociationRule>, String) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>, Object) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRulesProducer - Interface in weka.associations: Interface to something that can provide a list of AssociationRules.
AssociationRuleVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize association results in the explorer.
AssociationsPanel - Class in weka.gui.explorer: This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel() - Constructor for class weka.gui.explorer.AssociationsPanel: Creates the associator panel
Associator - Interface in weka.associations
Associator - Class in weka.gui.beans: Bean that wraps around weka.associations.
Associator() - Constructor for class weka.gui.beans.Associator: Creates a new Associator instance.
AssociatorBeanInfo - Class in weka.gui.beans: BeanInfo class for the Associator wrapper bean
AssociatorBeanInfo() - Constructor for class weka.gui.beans.AssociatorBeanInfo
AssociatorCustomizer - Class in weka.gui.beans: GUI customizer for the associator wrapper bean
AssociatorCustomizer() - Constructor for class weka.gui.beans.AssociatorCustomizer
AssociatorEvaluation - Class in weka.associations: Class for evaluating Associaters.
AssociatorEvaluation() - Constructor for class weka.associations.AssociatorEvaluation: default constructor
associatorTipText() - Method in class weka.associations.SingleAssociatorEnhancer: Returns the tip text for this property
ATT_ARRAY - Static variable in class weka.core.xml.XMLSerialization: the tag whether array or not (yes/no)
ATT_ARRAY_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_ARRAY
ATT_CLASS - Static variable in class weka.core.xml.XMLInstances: the class attribute
ATT_CLASS - Static variable in class weka.core.xml.XMLSerialization: the tag for the class
ATT_FORMAT - Static variable in class weka.core.xml.XMLInstances: the format attribute (for date attributes)
ATT_INDEX - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the index attribute.
ATT_INDEX - Static variable in class weka.core.xml.XMLInstances: the index attribute
ATT_MISSING - Static variable in class weka.core.xml.XMLInstances: the missing attribute
ATT_NAME - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLDocument: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLOptions: the name attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLSerialization: the tag for the name
ATT_NULL - Static variable in class weka.core.xml.XMLSerialization: the tag whether null or not (yes/no)
ATT_NULL_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_NULL
ATT_PREDICTED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted attribute.
ATT_PRIMITIVE - Static variable in class weka.core.xml.XMLSerialization: the tag whether primitive or not (yes/no)
ATT_PRIMITIVE_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_PRIMITIVE
ATT_TYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "type" attribute.
ATT_TYPE - Static variable in class weka.core.xml.XMLInstances: the type attribute
ATT_TYPE - Static variable in class weka.core.xml.XMLOptions: the type attribute.
ATT_VALUE - Static variable in class weka.core.xml.XMLOptions: the value attribute.
ATT_VERSION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLDocument: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLInstances: the version attribute
ATT_VERSION - Static variable in class weka.core.xml.XMLSerialization: the version attribute
ATT_WEIGHT - Static variable in class weka.core.xml.XMLInstances: the weight attribute
attIndex() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.C45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns index of attribute for which split was generated.
attList_IrrTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
attribute(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index.
Attribute - Class in weka.core: Class for handling an attribute.
Attribute(String) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute.
Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute, where metadata is supplied.
Attribute(String, String) - Constructor for class weka.core.Attribute: Constructor for a date attribute.
Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a date attribute, where metadata is supplied.
Attribute(String, List<String>) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes.
Attribute(String, List<String>, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes, where metadata is supplied.
Attribute(String, Instances) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, Instances, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, int) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute with a particular index.
Attribute(String, String, int) - Constructor for class weka.core.Attribute: Constructor for date attributes with a particular index.
Attribute(String, List<String>, int) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes with a particular index.
Attribute(String, Instances, int) - Constructor for class weka.core.Attribute: Constructor for a relation-valued attribute with a particular index.
attribute(int) - Method in interface weka.core.Instance: Returns the attribute with the given index.
attribute(int) - Method in class weka.core.Instances: Returns an attribute.
attribute(String) - Method in class weka.core.Instances: Returns an attribute given its name.
Attribute - Class in weka.core.pmml.jaxbbindings: Java class for Attribute element declaration.
Attribute() - Constructor for class weka.core.pmml.jaxbbindings.Attribute
ATTRIBUTE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
attributeAsClass() - Method in class weka.gui.arffviewer.ArffPanel: sets the current attribute as class attribute, i.e.
attributeAsClass() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the current selected Attribute as class attribute, i.e.
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets the attribute at the given col index as the new class attribute
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: sets the attribute at the given col index as the new class attribute, i.e.
attributeCaseFix(String) - Method in class weka.experiment.DatabaseUtils: returns key column headings in their original case.
attributeCaseFix(String) - Method in interface weka.experiment.InstanceQueryAdapter: returns key column headings in their original case.
AttributeEvaluator - Interface in weka.attributeSelection: Interface for classes that evaluate attributes individually.
AttributeExpression - Class in weka.core: A general purpose class for parsing mathematical expressions involving attribute values.
AttributeExpression() - Constructor for class weka.core.AttributeExpression
attributeIndexesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
AttributeListPanel - Class in weka.gui: Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
AttributeListPanel() - Constructor for class weka.gui.AttributeListPanel: Creates the attribute selection panel with no initial instances.
AttributeLocator - Class in weka.core: This class locates and records the indices of a certain type of attributes, recursively in case of Relational attributes.
AttributeLocator(Instances, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int[]) - Constructor for class weka.core.AttributeLocator: initializes the AttributeLocator with the given data for the specified type of attribute.
attributeNamePrefixTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
attributeNames() - Method in class weka.classifiers.functions.SMO: Returns the attribute names.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the tip text for this property
AttributePanel - Class in weka.gui.visualize: This panel displays one dimensional views of the attributes in a dataset.
AttributePanel() - Constructor for class weka.gui.visualize.AttributePanel
AttributePanel(Color) - Constructor for class weka.gui.visualize.AttributePanel: This constructs an attributePanel.
AttributePanelEvent - Class in weka.gui.visualize: Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int) - Constructor for class weka.gui.visualize.AttributePanelEvent: Constructor
AttributePanelListener - Interface in weka.gui.visualize: Interface for classes that want to listen for Attribute selection changes in the attribute panel
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToNominal
ATTRIBUTES - Static variable in class weka.core.json.JSONInstances: the attributes object.
AttributeSelectedClassifier - Class in weka.classifiers.meta: Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
AttributeSelectedClassifier() - Constructor for class weka.classifiers.meta.AttributeSelectedClassifier: Default constructor.
AttributeSelection - Class in weka.attributeSelection: Attribute selection class.
AttributeSelection() - Constructor for class weka.attributeSelection.AttributeSelection: constructor.
AttributeSelection - Class in weka.filters.supervised.attribute: A supervised attribute filter that can be used to select attributes.
AttributeSelection() - Constructor for class weka.filters.supervised.attribute.AttributeSelection: Constructor
attributeSelectionChange(AttributePanelEvent) - Method in interface weka.gui.visualize.AttributePanelListener: Called when the user clicks on an attribute bar
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
AttributeSelectionPanel - Class in weka.gui: Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel() - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel(boolean, boolean, boolean, boolean) - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel - Class in weka.gui.explorer: This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel() - Constructor for class weka.gui.explorer.AttributeSelectionPanel: Creates the classifier panel
AttributeSetEvaluator - Class in weka.attributeSelection: Abstract attribute set evaluator.
AttributeSetEvaluator() - Constructor for class weka.attributeSelection.AttributeSetEvaluator
attributeSparse(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index in the sparse representation.
attributeSparse(int) - Method in interface weka.core.Instance: Returns the attribute with the given index in the sparse representation.
attributeSpecsTipText() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns the tip text for this property.
AttributeStats - Class in weka.core: A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats() - Constructor for class weka.core.AttributeStats
attributeStats(int) - Method in class weka.core.Instances: Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributesTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
attributesTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
attributesToString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Make a string from the attribues list.
AttributeSummarizer - Class in weka.gui.beans: Bean that encapsulates displays bar graph summaries for attributes in a data set.
AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer: Creates a new AttributeSummarizer instance.
AttributeSummarizerBeanInfo - Class in weka.gui.beans: Bean info class for the attribute summarizer bean
AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo
AttributeSummarizerCustomizer - Class in weka.gui.beans: GUI customizer for attribute summarizer.
AttributeSummarizerCustomizer() - Constructor for class weka.gui.beans.AttributeSummarizerCustomizer: Constructor
AttributeSummaryPanel - Class in weka.gui: This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class weka.gui.AttributeSummaryPanel: Creates the instances panel with no initial instances.
attributeToDoubleArray(int) - Method in class weka.core.Instances: Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer - Interface in weka.attributeSelection: Abstract attribute transformer.
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the tip text for this property
attributeTypeToString(int) - Static method in class weka.core.CheckScheme: returns a string representation of the attribute type
AttributeVisualizationPanel - Class in weka.gui: Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor.
attrIndexRangeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Finds the best splitting point for an attribute in the instances
autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
AVERAGE_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Average of Probabilities
AveragingResultProducer - Class in weka.experiment: Takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer() - Constructor for class weka.experiment.AveragingResultProducer
avgCost() - Method in class weka.classifiers.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgCost() - Method in class weka.classifiers.evaluation.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the average transformation probability

B

B_ENTROPY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
B_SPHERE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: Blend setting modes
backQuoteChars(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
BACKUP_EXTENSION - Static variable in class weka.gui.scripting.Script: the backup extension.
Bagging - Class in weka.classifiers.meta: Class for bagging a classifier to reduce variance.
Bagging() - Constructor for class weka.classifiers.meta.Bagging: Constructor.
bagSizePercentTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
balanceClassTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property
BallNode - Class in weka.core.neighboursearch.balltrees: Class representing a node of a BallTree.
BallNode(int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Constructor.
BallNode(int, int, int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallNode(int, int, int, Instance, double) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallSplitter - Class in weka.core.neighboursearch.balltrees: Abstract class for splitting a ball tree's BallNode.
BallSplitter() - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: default constructor.
BallSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: Creates a new instance of BallSplitter.
ballSplitterTipText() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns the tip text for this property.
BallTree - Class in weka.core.neighboursearch: Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference.
BallTree() - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTree(Instances) - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTreeConstructor - Class in weka.core.neighboursearch.balltrees: Abstract class for constructing a BallTree .
BallTreeConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BallTreeConstructor: Creates a new instance of BallTreeConstructor.
ballTreeConstructorTipText() - Method in class weka.core.neighboursearch.BallTree: Returns the tip text for this property.
BaseCumHazardTables - Class in weka.core.pmml.jaxbbindings: Java class for BaseCumHazardTables element declaration.
BaseCumHazardTables() - Constructor for class weka.core.pmml.jaxbbindings.BaseCumHazardTables
Baseline - Class in weka.core.pmml.jaxbbindings: Java class for Baseline element declaration.
Baseline() - Constructor for class weka.core.pmml.jaxbbindings.Baseline
BaselineCell - Class in weka.core.pmml.jaxbbindings: Java class for BaselineCell element declaration.
BaselineCell() - Constructor for class weka.core.pmml.jaxbbindings.BaselineCell
BaselineModel - Class in weka.core.pmml.jaxbbindings: Java class for BaselineModel element declaration.
BaselineModel() - Constructor for class weka.core.pmml.jaxbbindings.BaselineModel
BaselineStratum - Class in weka.core.pmml.jaxbbindings: Java class for BaselineStratum element declaration.
BaselineStratum() - Constructor for class weka.core.pmml.jaxbbindings.BaselineStratum
BASELINETESTSTATISTIC - Enum in weka.core.pmml.jaxbbindings: Java class for BASELINE-TEST-STATISTIC.
baseTipText() - Method in class weka.core.neighboursearch.CoverTree: Returns the tip text for this property.
BATCH - Static variable in interface weka.core.converters.Loader
BATCH - Static variable in interface weka.core.converters.Saver
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent: Specifies that the batch of instances is finished
BatchAssociationRulesEvent - Class in weka.gui.beans: Class encapsulating a set of association rules.
BatchAssociationRulesEvent(Object, AssociationRules) - Constructor for class weka.gui.beans.BatchAssociationRulesEvent: Creates a new BatchAssociationRulesEvent instance.
BatchAssociationRulesListener - Interface in weka.gui.beans: Interface to something that can process a BatchAssociationRulesEvent.
BatchClassifierEvent - Class in weka.gui.beans: Class encapsulating a built classifier and a batch of instances to test on.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierListener - Interface in weka.gui.beans: Interface to something that can process a BatchClassifierEvent
BatchClustererEvent - Class in weka.gui.beans: Class encapsulating a built clusterer and a batch of instances to test on.
BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - Constructor for class weka.gui.beans.BatchClustererEvent: Creates a new BatchClustererEvent instance.
BatchClustererListener - Interface in weka.gui.beans: Interface to something that can process a BatchClustererEvent
BatchConverter - Interface in weka.core.converters: Marker interface for a loader/saver that can retrieve instances in batch mode
batchFilterFile(Filter, String[]) - Static method in class weka.filters.Filter: Method for testing filters ability to process multiple batches.
batchFinished() - Method in class weka.filters.Filter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.MultiFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleBatchFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleStreamFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.PartitionMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SpreadSubsample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddCluster: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddID: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddNoise: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Center: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.MathExpression: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.NominalToString: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Normalize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveType: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Standardize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Randomize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveRange: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceJoiner: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceSavePanel
batchFinished() - Method in class weka.gui.streams.InstanceTable
batchFinished() - Method in class weka.gui.streams.InstanceViewer
BatchPredictor - Interface in weka.core: Interface to something that can produce predictions in a batch manner when presented with a set of Instances.
BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable: score types
BayesInput - Class in weka.core.pmml.jaxbbindings: Java class for BayesInput element declaration.
BayesInput() - Constructor for class weka.core.pmml.jaxbbindings.BayesInput
BayesInputs - Class in weka.core.pmml.jaxbbindings: Java class for BayesInputs element declaration.
BayesInputs() - Constructor for class weka.core.pmml.jaxbbindings.BayesInputs
BayesNet - Class in weka.classifiers.bayes: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet
BayesNet - Static variable in interface weka.core.Drawable
BayesNet - Class in weka.datagenerators.classifiers.classification: Generates random instances based on a Bayes network.
BayesNet() - Constructor for class weka.datagenerators.classifiers.classification.BayesNet: initializes the generator
BayesNetEstimator - Class in weka.classifiers.bayes.net.estimate: BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
BayesNetEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BayesNetEstimator
BayesNetGenerator - Class in weka.classifiers.bayes.net: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNetGenerator() - Constructor for class weka.classifiers.bayes.net.BayesNetGenerator: Constructor for BayesNetGenerator.
BayesOutput - Class in weka.core.pmml.jaxbbindings: Java class for BayesOutput element declaration.
BayesOutput() - Constructor for class weka.core.pmml.jaxbbindings.BayesOutput
BDeu - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance
BeanCommon - Interface in weka.gui.beans: Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to exercise some control over connections.
BeanConnection - Class in weka.gui.beans: Class for encapsulating a connection between two beans.
BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor, Integer...) - Constructor for class weka.gui.beans.BeanConnection: Creates a new BeanConnection instance.
BeanCustomizer - Interface in weka.gui.beans: Extends java.beans.Customizer and provides a method to register a listener interested in notification about whether the customizer has modified the object that it is customizing.
BeanCustomizer.ModifyListener - Interface in weka.gui.beans: Interface for something that is interested in the modified status of a source object (typically a BeanCustomizer that is editing an object)
BeanInstance - Class in weka.gui.beans: Class that manages a set of beans.
BeanInstance(JComponent, Object, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance.
BeanInstance(JComponent, String, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance given the fully qualified name of the bean
BeansProperties - Class in weka.gui.beans: Utility class encapsulating various properties for the KnowledgeFlow and providing methods to register and deregister plugin Bean components
BeansProperties() - Constructor for class weka.gui.beans.BeansProperties
BeanVisual - Class in weka.gui.beans: BeanVisual encapsulates icons and label for a given bean.
BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual: Constructor
BestFirst - Class in weka.attributeSelection: BestFirst:

Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
BestFirst() - Constructor for class weka.attributeSelection.BestFirst: Constructor
BestFirst.Link2 - Class in weka.attributeSelection: Class for a node in a linked list.
BestFirst.Link2(Object[], double) - Constructor for class weka.attributeSelection.BestFirst.Link2: Constructor
BestFirst.LinkedList2 - Class in weka.attributeSelection: Class for handling a linked list.
BestFirst.LinkedList2(int) - Constructor for class weka.attributeSelection.BestFirst.LinkedList2
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Return the best split
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
bias() - Method in class weka.classifiers.functions.SGDText
bias() - Method in class weka.classifiers.functions.SMO: Returns the bias of each binary SMO.
biasToUniformClassTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
BIBTEX_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the end comment tag for inserting the generated BibTex
BIBTEX_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the start comment tag for inserting the generated BibTex
BIFFileTipText() - Method in class weka.classifiers.bayes.BayesNet
BIFFormatException - Exception in weka.gui.graphvisualizer: This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
BIFFormatException(String) - Constructor for exception weka.gui.graphvisualizer.BIFFormatException
BIFParser - Class in weka.gui.graphvisualizer: This class parses an inputstream or a string in XMLBIF ver.
BIFParser(String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is a String)
BIFParser(InputStream, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is an InputStream)
BIFReader - Class in weka.classifiers.bayes.net: Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.

For more details on XML BIF see:

Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).
BIFReader() - Constructor for class weka.classifiers.bayes.net.BIFReader: the default constructor
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the tip text for this property
BINARY - Static variable in class weka.gui.beans.SerializedModelSaver
binaryAttributesNominalTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
BinaryItem - Class in weka.associations: Class that encapsulates an item whose backing Attribute is binary or unary.
BinaryItem(Attribute, int) - Constructor for class weka.associations.BinaryItem: Constructor.
BinarySimilarity - Class in weka.core.pmml.jaxbbindings: Java class for binarySimilarity element declaration.
BinarySimilarity() - Constructor for class weka.core.pmml.jaxbbindings.BinarySimilarity
BinarySparseInstance - Class in weka.core: Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(Instance) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given instance.
BinarySparseInstance(SparseInstance) - Constructor for class weka.core.BinarySparseInstance: Constructor that copies the info from the given instance.
BinarySparseInstance(double, double[]) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given parameters.
BinarySparseInstance(double, int[], int) - Constructor for class weka.core.BinarySparseInstance: Constructor that inititalizes instance variable with given values.
BinarySparseInstance(int) - Constructor for class weka.core.BinarySparseInstance: Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
binarySplitsTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
binaryToKOML(String, String) - Static method in class weka.core.xml.SerialUIDChanger: converts a binary file into a KOML XML file
BinC45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45ModelSelection: Initializes the split selection method with the given parameters.
BinC45Split - Class in weka.classifiers.trees.j48: Class implementing a binary C4.5-like split on an attribute.
BinC45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45Split: Initializes the split model.
binomialStandardError(double, int) - Static method in class weka.core.Statistics: Computes standard error for observed values of a binomial random variable.
binRangePrecisionTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
BIRCHCluster - Class in weka.datagenerators.clusterers: Cluster data generator designed for the BIRCH System

Dataset is generated with instances in K clusters.
Instances are 2-d data points.
Each cluster is characterized by the number of data points in itits radius and its center.
BIRCHCluster() - Constructor for class weka.datagenerators.clusterers.BIRCHCluster: initializes the generator with default values
BIRD_IMAGE1 - Static variable in class weka.core.RepositoryIndexGenerator
BIRD_IMAGE2 - Static variable in class weka.core.RepositoryIndexGenerator
blocker(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
BMAEstimator - Class in weka.classifiers.bayes.net.estimate: BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
BMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BMAEstimator
BMPWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a BMP-file.
BMPWriter() - Constructor for class weka.gui.visualize.BMPWriter: initializes the object.
BMPWriter(JComponent) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component.
BMPWriter(JComponent, File) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component and filename.
BOOL - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BOOL used for reading experiment results.
BOOLEAN - Static variable in interface weka.core.json.sym
BOOLEAN - Static variable in interface weka.core.mathematicalexpression.sym
BOOLEAN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
booleanColsTipText() - Method in class weka.datagenerators.ClusterGenerator: Returns the tip text for this property
BottomUpConstructor - Class in weka.core.neighboursearch.balltrees: The class that constructs a ball tree bottom up.
BottomUpConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BottomUpConstructor: Creates a new instance of BottomUpConstructor.
BoundaryPanel - Class in weka.gui.boundaryvisualizer: BoundaryPanel.
BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel: Creates a new BoundaryPanel instance.
BoundaryPanelDistributed - Class in weka.gui.boundaryvisualizer: This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
BoundaryPanelDistributed(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Creates a new BoundaryPanelDistributed instance.
BoundaryValueMeans - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValueMeans element declaration.
BoundaryValueMeans() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValueMeans
BoundaryValues - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValues element declaration.
BoundaryValues() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValues
BoundaryVisualizer - Class in weka.gui.boundaryvisualizer: BoundaryVisualizer.
BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new BoundaryVisualizer instance.
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.Split: Returns the name of the branch that the supplied instance would go down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.SplitNode: Return the branch that the supplied instance goes down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
breakUp(String, int) - Static method in class weka.core.Utils: Breaks up the string, if wider than "columns" characters.
BrowserHelper - Class in weka.gui: A little helper class for browser related stuff.
BrowserHelper() - Constructor for class weka.gui.BrowserHelper
bufferSizeTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
build(String, String) - Method in class weka.gui.HierarchyPropertyParser: Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori: Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in interface weka.associations.Associator: Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.FilteredAssociator: Build the associator on the filtered data.
buildAssociations(Instances) - Method in class weka.associations.FPGrowth: Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayes: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Generates the classifier.
buildClassifier(Instances) - Method in interface weka.classifiers.Classifier: Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcesses: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegression: Builds a regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Logistic: Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron: Call this function to build and train a neural network for the training data provided.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGD: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGDText: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLogistic: Builds the logistic regression using LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMO: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMOreg: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: learn SVM parameters from data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMO: learn SVM parameters from data using Smola's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: learn SVM parameters from data using Keerthi's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.VotedPerceptron: Builds the ensemble of perceptrons.
buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Stump method for building the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IBk: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.KStar: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1: Boosting method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression: Build the classifier on the supplied data
buildClassifier(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Build the classifier on the dimensionally reduced data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Bagging: Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CVParameterSelection: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiScheme: Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee: Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomSubSpace: builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RegressionByDiscretization: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking: Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote: Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Build the classifier
buildClassifier(Instances) - Method in class weka.classifiers.misc.SerializedClassifier: loads only the serialized classifier
buildClassifier(Instances) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Throw an exception - PMML models are pre-built.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.JRip: Builds Ripper in the order of class frequencies.
buildClassifier(Instances) - Method in class weka.classifiers.rules.OneR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.PART: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.part.MakeDecList: Builds dec list.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.HoeffdingTree: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Builds the classifier split model for the given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Method for building a classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Method for building a naive bayes classifier tree
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Build the no-split node
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Creates a NBTree-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Creates a "no-split"-split for a given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LMT: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building a logistic model tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase: Builds the logistic regression model usiing LogitBoost.
buildClassifier(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Builds the split.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule: Generates a single rule or m5 model tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode: Build this node (find an attribute and split point)
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomForest: Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree: Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree: Builds classifier.
buildClusterer(Instances) - Method in class weka.clusterers.AbstractClusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Canopy
buildClusterer(Instances) - Method in interface weka.clusterers.Clusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Cobweb: Builds the clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.EM: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FarthestFirst: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FilteredClusterer: Build the clusterer on the filtered data.
buildClusterer(Instances) - Method in class weka.clusterers.HierarchicalClusterer
buildClusterer(Instances) - Method in class weka.clusterers.MakeDensityBasedClusterer: Builds a clusterer for a set of instances.
buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans: Generates a clusterer.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList: Builds the partial tree without hold out set.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList: Builds the partial tree without hold out set.
buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList: Builds the partial tree with hold out set
buildEstimator(Estimator, String[], boolean) - Static method in class weka.estimators.Estimator: Build an estimator using the options.
buildEstimator(Estimator, Instances, int, int, int, boolean) - Static method in class weka.estimators.Estimator
buildEvaluator(Instances) - Method in class weka.attributeSelection.ASEvaluation: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CfsSubsetEval: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CorrelationAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.GainRatioAttributeEval: Initializes a gain ratio attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.InfoGainAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.OneRAttributeEval: Initializes a OneRAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Initializes principal components and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.ReliefFAttributeEval: Initializes a ReliefF attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.WrapperSubsetEval: Generates a attribute evaluator.
buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Build the data generator
buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Initialize the generator using the supplied instances
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.CachedKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Kernel: builds the kernel with the given data
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Puk: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.RBFKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.StringKernel: builds the kernel with the given data.
buildLogisticModelsTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
buildRegressionTreeTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
buildRule(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for building a pruned partial tree.
buildRule(Instances, Instances) - Method in class weka.classifiers.rules.part.PruneableDecList: Method for building a pruned partial tree.
buildStructure() - Method in class weka.classifiers.bayes.BayesNet: buildStructure determines the network structure/graph of the network.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: buildStructure determines the network structure/graph of the network.
buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure.
buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure with hold out set
buildTree(Instances, SimpleLinearRegression[][], double, double, Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building the tree structure.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Builds the ball tree.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Builds the ball tree bottom up.
buildTree() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Builds a ball tree middle out.
buildTree() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Builds the ball tree top down.
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.Evaluation
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.evaluation.Evaluation
BuiltInArithmetic - Class in weka.core.pmml: Built-in function for +, -, *, /.
BuiltInArithmetic(BuiltInArithmetic.Operator) - Constructor for class weka.core.pmml.BuiltInArithmetic: Construct a new Arithmetic built-in pmml function.
BuiltInMath - Class in weka.core.pmml: Built-in function for min, max, sum, avg, log10, ln, sqrt, abs, exp, pow, threshold, floor, ceil and round.
BuiltInMath(BuiltInMath.MathFunc) - Constructor for class weka.core.pmml.BuiltInMath: Construct a new built-in pmml Math function.
BuiltInString - Class in weka.core.pmml: Built-in function for uppercase, substring and trimblanks.
BVDecompose - Class in weka.classifiers: Class for performing a Bias-Variance decomposition on any classifier using the method specified in:

Ron Kohavi, David H.
BVDecompose() - Constructor for class weka.classifiers.BVDecompose
BVDecomposeSegCVSub - Class in weka.classifiers: This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).
The Kohavi and Wolpert definition of bias and variance is specified in (2).
The Webb definition of bias and variance is specified in (3).

Geoffrey I.
BVDecomposeSegCVSub() - Constructor for class weka.classifiers.BVDecomposeSegCVSub
BYTE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BYTE used for reading experiment results.

C

C45Loader - Class in weka.core.converters: Reads a file that is C45 format.
C45Loader() - Constructor for class weka.core.converters.C45Loader
C45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-type split for a given dataset.
C45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45ModelSelection: Initializes the split selection method with the given parameters.
C45PruneableClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree: Constructor for pruneable tree structure.
C45PruneableDecList - Class in weka.classifiers.rules.part: Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
C45PruneableDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.C45PruneableDecList: Constructor for pruneable tree structure.
C45Saver - Class in weka.core.converters: Writes to a destination that is in the format used by the C4.5 algorithm.
Therefore it outputs a names and a data file.
C45Saver() - Constructor for class weka.core.converters.C45Saver: Constructor
C45Split - Class in weka.classifiers.trees.j48: Class implementing a C4.5-type split on an attribute.
C45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.C45Split: Initializes the split model.
CachedKernel - Class in weka.classifiers.functions.supportVector: Base class for RBFKernel and PolyKernel that implements a simple LRU.
CachedKernel() - Constructor for class weka.classifiers.functions.supportVector.CachedKernel: default constructor - does nothing.
cacheKeyNameTipText() - Method in class weka.experiment.DatabaseResultListener: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
calcCentroidPivot(int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcCentroidPivot(int, int, int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcColumnWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the column of the given table.
calcFullMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
calcGraph(int, int) - Method in class weka.gui.AttributeVisualizationPanel: Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the header of the given table.
calcMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator: Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
calcPivot(BallNode, BallNode, Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the centroid pivot of a node based on its two child nodes.
calcPivot(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: /** Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the centroid pivot of a node based on the list of points that it contains (tbe two lists of its children are provided).
calcRadius(int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of node.
calcRadius(int, int, int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node.
calcRadius(BallNode, BallNode, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the radius of a node based on its two child nodes.
calcRadius(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instance, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on the list of points that it contains (the two lists of its children are provided).
calcScore(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: performCV returns the accuracy calculated using cross validation.
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Added Parent
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With AddedParent
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithReversedParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Arrow reversed
calculateAdjRSquared(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the adjusted R-squared value for a linear regression model.
calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode: Updates the alpha field for all nodes.
calculateDerived() - Method in class weka.experiment.PairedStats: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.PairedStatsCorrected: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.Stats: Tells the object to calculate any statistics that don't have their values automatically updated during add.
calculateFStat(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the F-statistic for a linear regression model.
calculateRSquared(Instances, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the R-squared value for a linear regression model, where sum of squared residuals is already calculated.
calculateSSR(Instances, Attribute, double, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the sum of squared residuals of the simple linear regression model: y = a + bx.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedCorrectedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in interface weka.experiment.Tester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStdDevsTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
calculateStdErrorOfCoef(Instances, Attribute, double, double, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the standard errors of slope and intercept for a simple linear regression model: y = a + bx.
calculateStdErrorOfCoef(Instances, boolean[], double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the standard errors of the coefficients in a multiple linear regression.
calculateTStats(double[], double[], int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the t-statistic of each coefficient in a multiple linear regression model.
canAcceptConnection(Class<?>) - Method in class weka.gui.beans.MetaBean: Checks to see if any of the inputs to this group implements the supplied listener class
cancel() - Method in class weka.core.converters.AbstractFileSaver: Cancels the incremental saving process.
cancel() - Method in class weka.core.converters.AbstractSaver: Cancels the incremental saving process if the write mode is CANCEL.
cancel() - Method in class weka.core.converters.DatabaseSaver: Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
CANCEL_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies a cancelled property selection.
CANCEL_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies a cancelled property selection
canMoveDown(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved down
canMoveUp(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved up
Canopy - Class in weka.clusterers: Cluster data using the capopy clustering algorithm, which requires just one pass over the data.
Canopy() - Constructor for class weka.clusterers.Canopy
CANOPY - Static variable in class weka.clusterers.SimpleKMeans
canopyMaxNumCanopiesToHoldInMemoryTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyMinimumCanopyDensityTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyPeriodicPruningRateTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyT1TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canopyT2TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canPlot(boolean) - Method in class weka.gui.explorer.AbstractPlotInstances: Returns whether all the data is available and the plot instances can be used for plotting.
canProduceRules() - Method in class weka.associations.Apriori: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in interface weka.associations.AssociationRulesProducer: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FilteredAssociator: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FPGrowth: Returns true if this AssociationRulesProducer can actually produce rules.
canRedo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in interface weka.core.Undoable: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffPanel: returns whether an undo is possible
canUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether an undo is possible, i.e.
Capabilities - Class in weka.core: A class that describes the capabilites (e.g., handling certain types of attributes, missing values, types of classes, etc.) of a specific classifier.
Capabilities(CapabilitiesHandler) - Constructor for class weka.core.Capabilities: initializes the capabilities for the given owner
capabilities() - Method in class weka.core.Capabilities: Returns an Iterator over the stored capabilities
Capabilities.Capability - Enum in weka.core: enumeration of all capabilities
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AssociationsPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AttributeSelectionPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClassifierPanel: method gets called in case of a change event.
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClustererPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in interface weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.PreprocessPanel: method gets called in case of a change event
CapabilitiesHandler - Interface in weka.core: Classes implementing this interface return their capabilities in regards to datasets.
capacity() - Method in class weka.core.matrix.DoubleVector: Gets the capacity of the vector.
capacity() - Method in class weka.core.matrix.IntVector: Returns the capacity of the vector
cardinalityTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the tip text for this property
caretUpdate(CaretEvent) - Method in class weka.gui.LogWindow: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.ConnectionPanel: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.QueryPanel: Called when the caret position is updated.
carTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
CARuleMiner - Interface in weka.associations: Interface for learning class association rules.
cast(Object) - Static method in class weka.core.Utils: Casting an object without "unchecked" compile-time warnings.
cat(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Combine two vectors together
CategoricalPredictor - Class in weka.core.pmml.jaxbbindings: Java class for CategoricalPredictor element declaration.
CategoricalPredictor() - Constructor for class weka.core.pmml.jaxbbindings.CategoricalPredictor
Categories - Class in weka.core.pmml.jaxbbindings: Java class for Categories element declaration.
Categories() - Constructor for class weka.core.pmml.jaxbbindings.Categories
Category - Class in weka.core.pmml.jaxbbindings: Java class for Category element declaration.
Category() - Constructor for class weka.core.pmml.jaxbbindings.Category
CATSCORINGMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for CAT-SCORING-METHOD.
CEIL - Static variable in interface weka.core.mathematicalexpression.sym
CEIL - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
Center - Class in weka.filters.unsupervised.attribute: Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
Center() - Constructor for class weka.filters.unsupervised.attribute.Center
centerDataTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property
centerHorizontal(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between left and right most node in the list
centerInstances(Instances, int[], double) - Method in class weka.core.neighboursearch.KDTree: Assigns instances to centers using KDTree.
centerVertical(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between top and bottom most node in the list
CfsSubsetEval - Class in weka.attributeSelection: CfsSubsetEval :

Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

For more information see:

M.
CfsSubsetEval() - Constructor for class weka.attributeSelection.CfsSubsetEval: Constructor
ChangeDateFormat - Class in weka.filters.unsupervised.attribute: Changes the date format used by a date attribute.
ChangeDateFormat() - Constructor for class weka.filters.unsupervised.attribute.ChangeDateFormat
changeLength(double) - Method in class weka.core.AlgVector: Changes the length of a vector.
changeUID(long, long, String, String) - Static method in class weka.core.xml.SerialUIDChanger: changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
CharacterDelimitedTokenizer - Class in weka.core.tokenizers: Abstract superclass for tokenizers that take characters as delimiters.
CharacterDelimitedTokenizer() - Constructor for class weka.core.tokenizers.CharacterDelimitedTokenizer
Characteristic - Class in weka.core.pmml.jaxbbindings: Java class for Characteristic element declaration.
Characteristic() - Constructor for class weka.core.pmml.jaxbbindings.Characteristic
Characteristics - Class in weka.core.pmml.jaxbbindings: Java class for Characteristics element declaration.
Characteristics() - Constructor for class weka.core.pmml.jaxbbindings.Characteristics
charSetTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
ChartEvent - Class in weka.gui.beans: Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object, Vector<String>, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
chartingEvalWindowSizeTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Return a tip text string for this property
ChartListener - Interface in weka.gui.beans: Interface to something that can process a ChartEvent
Chebychev - Class in weka.core.pmml.jaxbbindings: Java class for chebychev element declaration.
Chebychev() - Constructor for class weka.core.pmml.jaxbbindings.Chebychev
ChebyshevDistance - Class in weka.core: Implements the Chebyshev distance.
ChebyshevDistance() - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object, Instances must be still set.
ChebyshevDistance(Instances) - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object and automatically initializes the ranges.
check(double) - Method in class weka.classifiers.trees.j48.Distribution: Checks if at least two bags contain a minimum number of instances.
Check - Class in weka.core: Abstract general class for testing in Weka.
Check() - Constructor for class weka.core.Check
CheckAssociator - Class in weka.associations: Class for examining the capabilities and finding problems with associators.
CheckAssociator() - Constructor for class weka.associations.CheckAssociator
CheckAttributeSelection - Class in weka.attributeSelection: Class for examining the capabilities and finding problems with attribute selection schemes.
CheckAttributeSelection() - Constructor for class weka.attributeSelection.CheckAttributeSelection
CheckBoxList - Class in weka.gui: An extended JList that contains CheckBoxes.
CheckBoxList() - Constructor for class weka.gui.CheckBoxList: initializes the list with an empty CheckBoxListModel
CheckBoxList(CheckBoxList.CheckBoxListModel) - Constructor for class weka.gui.CheckBoxList: initializes the list with the given CheckBoxListModel
CheckBoxList.CheckBoxListModel - Class in weka.gui: A specialized model.
CheckBoxList.CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: initializes the model with no data.
CheckBoxList.CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
CheckBoxList.CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
CheckBoxList.CheckBoxListRenderer - Class in weka.gui: A specialized CellRenderer for the CheckBoxList
CheckBoxList.CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer
checkCanonicalUserOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options stay the same after settting, getting and re-setting again
CheckClassifier - Class in weka.classifiers: Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
CheckClusterer - Class in weka.clusterers: Class for examining the capabilities and finding problems with clusterers.
CheckClusterer() - Constructor for class weka.clusterers.CheckClusterer: default constructor
checkDefaultOptions() - Method in class weka.core.CheckOptionHandler: checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
CheckEstimator - Class in weka.estimators: Class for examining the capabilities and finding problems with estimators.
CheckEstimator() - Constructor for class weka.estimators.CheckEstimator
CheckEstimator.AttrTypes - Class in weka.estimators: class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
CheckEstimator.EstTypes - Class in weka.estimators: public class that contains info about the chosen attribute type estimator work on one attribute only
CheckEstimator.EstTypes() - Constructor for class weka.estimators.CheckEstimator.EstTypes: Constructor
CheckEstimator.EstTypes(boolean, boolean, boolean) - Constructor for class weka.estimators.CheckEstimator.EstTypes: Constructor
CheckEstimator.PostProcessor - Class in weka.estimators: a class for postprocessing the test-data
CheckEstimator.PostProcessor() - Constructor for class weka.estimators.CheckEstimator.PostProcessor
checkForAttributeType(int) - Method in class weka.core.Instances: Checks for attributes of the given type in the dataset
checkForMissingClasses(Package, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks to see if there are any classes that we should try to instantiate before allowing this package to be loaded.
checkForMissingFiles(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks to see if there are any missing files/directories for a given package.
checkForNewPackages(PrintStream...) - Static method in class weka.core.WekaPackageManager: Check for new packages on the server and refresh the local cache if needed
checkForRemainingOptions(String[]) - Static method in class weka.core.Utils: Checks if the given array contains any non-empty options.
checkForStringAttributes() - Method in class weka.core.Instances: Checks for string attributes in the dataset
checkForUnsetEnvVar(Package, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks to see if there are any environment variables or properties that should be set at startup before allowing this package to be loaded.
checkGlobalInfo() - Method in class weka.core.CheckGOE: checks whether the object declares a globalInfo method.
CheckGOE - Class in weka.core: Simple command line checking of classes that are editable in the GOE.
CheckGOE() - Constructor for class weka.core.CheckGOE: default constructor
checkIndicesList(MiddleOutConstructor.MyIdxList, int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Checks whether if the points in an index list are in some specified of the master index array.
checkInstance(Instance) - Method in class weka.core.Instances: Checks if the given instance is compatible with this dataset.
CheckKernel - Class in weka.classifiers.functions.supportVector: Class for examining the capabilities and finding problems with kernels.
CheckKernel() - Constructor for class weka.classifiers.functions.supportVector.CheckKernel
checkListOptions() - Method in class weka.core.CheckOptionHandler: checks whether the listOptions method works
checkModel() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Checks if generated model is valid.
checkModel(int) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Checks if there are at least 2 subsets that contain >= minNumInstances.
CheckOptionHandler - Class in weka.core: Simple command line checking of classes that implement OptionHandler.
CheckOptionHandler() - Constructor for class weka.core.CheckOptionHandler
checkRemainingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed completely or some "left-over" options remain
checkResettingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the optionhandler can be re-setted again to default options after the user-supplied options have been set.
CheckScheme - Class in weka.core: Abstract general class for testing schemes in Weka.
CheckScheme() - Constructor for class weka.core.CheckScheme
CheckScheme.PostProcessor - Class in weka.core: a class for postprocessing the test-data
CheckScheme.PostProcessor() - Constructor for class weka.core.CheckScheme.PostProcessor
checkSetOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed at all
CheckSource - Class in weka.classifiers: A simple class for checking the source generated from Classifiers implementing the weka.classifiers.Sourcable interface.
CheckSource() - Constructor for class weka.classifiers.CheckSource
CheckSource - Class in weka.filters: A simple class for checking the source generated from Filters implementing the weka.filters.Sourcable interface.
CheckSource() - Constructor for class weka.filters.CheckSource
checkStatus(Object) - Method in interface weka.experiment.Compute: Check on the status of a Task
checkStatus(Object) - Method in class weka.experiment.RemoteEngine: Returns status information on a particular task
checksTurnedOffTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
checkToolTips() - Method in class weka.core.CheckGOE: checks whether the object declares tip text method for all its properties.
ChildParent - Class in weka.core.pmml.jaxbbindings: Java class for ChildParent element declaration.
ChildParent() - Constructor for class weka.core.pmml.jaxbbindings.ChildParent
childrenValues() - Method in class weka.gui.HierarchyPropertyParser: The value in the children nodes.
chisqDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: chi-squared
chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables: Returns chi-squared probability for a given matrix.
chiSquaredProbability(double, double) - Static method in class weka.core.Statistics: Returns chi-squared probability for given value and degrees of freedom.
chiVal(double[][], boolean) - Static method in class weka.core.ContingencyTables: Computes chi-squared statistic for a contingency table.
chol() - Method in class weka.core.matrix.Matrix: Cholesky Decomposition
CholeskyDecomposition - Class in weka.core.matrix: Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class weka.core.matrix.CholeskyDecomposition: Cholesky algorithm for symmetric and positive definite matrix.
chooseIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for choosing a subset to expand.
chooseLastIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Choose last index (ie.
CISearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci: The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
CISearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
CityBlock - Class in weka.core.pmml.jaxbbindings: Java class for cityBlock element declaration.
CityBlock() - Constructor for class weka.core.pmml.jaxbbindings.CityBlock
CLASS - Static variable in class weka.core.json.JSONInstances: the class attribute indicator.
CLASS_GROOVYCLASSLOADER - Static variable in class weka.core.scripting.Groovy: the classname of the Groovy classloader.
CLASS_IS_LAST - Static variable in class weka.core.TestInstances: can be used for settting the class attribute index to last
CLASS_PYTHONINERPRETER - Static variable in class weka.core.scripting.Jython: the classname of the Python interpreter
CLASS_PYTHONOBJECTINPUTSTREAM - Static variable in class weka.core.scripting.Jython: the classname of the Python ObjectInputStream
ClassAssigner - Class in weka.filters.unsupervised.attribute: Filter that can set and unset the class index.
ClassAssigner() - Constructor for class weka.filters.unsupervised.attribute.ClassAssigner
ClassAssigner - Class in weka.gui.beans: Bean that assigns a class attribute to a data set.
ClassAssigner() - Constructor for class weka.gui.beans.ClassAssigner
ClassAssignerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class assigner bean
ClassAssignerBeanInfo() - Constructor for class weka.gui.beans.ClassAssignerBeanInfo
ClassAssignerCustomizer - Class in weka.gui.beans: GUI customizer for the class assigner bean
ClassAssignerCustomizer() - Constructor for class weka.gui.beans.ClassAssignerCustomizer
classAttribute() - Method in class weka.core.AbstractInstance: Returns class attribute.
classAttribute() - Method in interface weka.core.Instance: Returns class attribute.
classAttribute() - Method in class weka.core.Instances: Returns the class attribute.
classAttributeNames() - Method in class weka.classifiers.functions.SMO
ClassCache - Class in weka.core: A singleton that stores all classes on the classpath.
ClassCache() - Constructor for class weka.core.ClassCache: Initializes the cache.
ClassCache.ClassFileFilter - Class in weka.core: For filtering classes.
ClassCache.ClassFileFilter() - Constructor for class weka.core.ClassCache.ClassFileFilter
ClassCache.DirectoryFilter - Class in weka.core: For filtering classes.
ClassCache.DirectoryFilter() - Constructor for class weka.core.ClassCache.DirectoryFilter
classColumnTipText() - Method in class weka.gui.beans.ClassAssigner: Tool tip text for this property
ClassDiscovery - Class in weka.core: This class is used for discovering classes that implement a certain interface or a derived from a certain class.
ClassDiscovery() - Constructor for class weka.core.ClassDiscovery
ClassDiscovery.StringCompare - Class in weka.core: compares two strings.
ClassDiscovery.StringCompare() - Constructor for class weka.core.ClassDiscovery.StringCompare
classDistributionIsPure() - Method in class weka.classifiers.trees.ht.HNode: Returns true if the class distribution is pure
classFirst(boolean) - Method in class weka.experiment.Experiment: Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classFlagTipText() - Method in class weka.datagenerators.ClusterGenerator: Returns the tip text for this property
ClassificationGenerator - Class in weka.datagenerators: Abstract class for data generators for classifiers.
ClassificationGenerator() - Constructor for class weka.datagenerators.ClassificationGenerator: initializes with default values
ClassificationViaRegression - Class in weka.classifiers.meta: Class for doing classification using regression methods.
ClassificationViaRegression() - Constructor for class weka.classifiers.meta.ClassificationViaRegression: Default constructor.
Classifier - Interface in weka.classifiers: Classifier interface.
Classifier - Class in weka.gui.beans: Bean that wraps around weka.classifiers
Classifier() - Constructor for class weka.gui.beans.Classifier: Creates a new Classifier instance.
ClassifierBeanInfo - Class in weka.gui.beans: BeanInfo class for the Classifier wrapper bean
ClassifierBeanInfo() - Constructor for class weka.gui.beans.ClassifierBeanInfo
ClassifierCustomizer - Class in weka.gui.beans: GUI customizer for the classifier wrapper bean
ClassifierCustomizer() - Constructor for class weka.gui.beans.ClassifierCustomizer
ClassifierDecList - Class in weka.classifiers.rules.part: Class for handling a rule (partial tree) for a decision list.
ClassifierDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.ClassifierDecList: Constructor - just calls constructor of class DecList.
ClassifierErrorsPlotInstances - Class in weka.gui.explorer: A class for generating plottable visualization errors.
ClassifierErrorsPlotInstances() - Constructor for class weka.gui.explorer.ClassifierErrorsPlotInstances
ClassifierPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
ClassifierPanel() - Constructor for class weka.gui.explorer.ClassifierPanel: Creates the classifier panel.
ClassifierPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Classifier panel and execute it.
ClassifierPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained classifiers
ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator
ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the classifier performance evaluator
ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
ClassifierPerformanceEvaluatorCustomizer - Class in weka.gui.beans: GUI customizer for the classifier performance evaluator component
ClassifierPerformanceEvaluatorCustomizer() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Constructor
classifiers() - Method in class weka.classifiers.meta.LogitBoost: Returns the array of classifiers that have been built.
ClassifierSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
ClassifierSplitEvaluator() - Constructor for class weka.experiment.ClassifierSplitEvaluator: No args constructor.
ClassifierSplitModel - Class in weka.classifiers.trees.j48: Abstract class for classification models that can be used recursively to split the data.
ClassifierSplitModel() - Constructor for class weka.classifiers.trees.j48.ClassifierSplitModel
classifiersTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
classifiersTipText() - Method in class weka.classifiers.MultipleClassifiersCombiner: Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
classifierTipText() - Method in class weka.classifiers.SingleClassifierEnhancer: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.RegressionSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
ClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure used for classification.
ClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.ClassifierTree: Constructor.
CLASSIFY_CHILD - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: Asks for another learning scheme to classify this node.
classifyInstance(Instance) - Method in class weka.classifiers.AbstractClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in interface weka.classifiers.Classifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcesses: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegression: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SMOreg: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression: Classify an instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a predicted class for the test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Vote: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
classifyInstance(Instance) - Method in class weka.classifiers.rules.OneR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.PART: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base: Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Predicts the class of the supplied instance using the linear model.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule: Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode: Classify an instance using this node.
classIndex() - Method in class weka.core.AbstractInstance: Returns the class attribute's index.
classIndex() - Method in interface weka.core.Instance: Returns the class attribute's index.
classIndex() - Method in class weka.core.Instances: Returns the class attribute's index.
classIndexTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.FilteredAssociator: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.LibSVMSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.SVMLightSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
classIsMissing() - Method in class weka.core.AbstractInstance: Tests if an instance's class is missing.
classIsMissing() - Method in interface weka.core.Instance: Tests if an instance's class is missing.
ClassLabels - Class in weka.core.pmml.jaxbbindings: Java class for ClassLabels element declaration.
ClassLabels() - Constructor for class weka.core.pmml.jaxbbindings.ClassLabels
ClassloaderUtil - Class in weka.core: Utility class that can add jar files to the classpath dynamically.
ClassloaderUtil() - Constructor for class weka.core.ClassloaderUtil
className(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the name of one of the classes.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
ClassOrder - Class in weka.filters.supervised.attribute: Changes the order of the classes so that the class values are no longer of in the order specified in the header.
ClassOrder() - Constructor for class weka.filters.supervised.attribute.ClassOrder
classOrderTipText() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the tip text for this property
ClassPanel - Class in weka.gui.visualize: This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
ClassPanel() - Constructor for class weka.gui.visualize.ClassPanel
ClassPanel(Color) - Constructor for class weka.gui.visualize.ClassPanel
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.BinC45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.C45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return the probability for a class value
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Return the probability for a class value
classProbLaplace(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
classValue() - Method in class weka.core.AbstractInstance: Returns an instance's class value in internal format.
classValue() - Method in interface weka.core.Instance: Returns an instance's class value as a floating-point number.
classValueIndexTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
ClassValuePicker - Class in weka.gui.beans
ClassValuePicker() - Constructor for class weka.gui.beans.ClassValuePicker
ClassValuePickerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class value picker bean
ClassValuePickerBeanInfo() - Constructor for class weka.gui.beans.ClassValuePickerBeanInfo
ClassValuePickerCustomizer - Class in weka.gui.beans
ClassValuePickerCustomizer() - Constructor for class weka.gui.beans.ClassValuePickerCustomizer
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.StringKernel: Frees the memory used by the kernel.
clean() - Method in interface weka.core.DistanceFunction: Free any references to training instances
clean() - Method in class weka.core.NormalizableDistance
cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Cleanup in order to save memory.
cleanUp() - Method in class weka.classifiers.rules.RuleStats: Frees up memory after classifier has been built.
cleanup() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.C45ModelSelection: Sets reference to training data to null.
cleanup(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.lmt.LogisticBase: Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Method not in use
cleanUp() - Method in class weka.clusterers.Canopy: Save memory
cleanUp() - Method in class weka.gui.explorer.AbstractPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: For freeing up memory.
clear() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Clears this hashtable so that it contains no keys.
clear() - Method in class weka.classifiers.xml.XMLClassifier: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.neighboursearch.covertrees.Stack: Removes all the elements from the stack.
clear() - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
clear() - Method in class weka.core.Stopwords: removes all stopwords
clear() - Method in class weka.core.Tee: removes all streams and places the default printstream, if any, again in the list.
clear() - Method in class weka.core.Trie: Removes all of the elements from this collection
clear() - Method in class weka.core.xml.MethodHandler: removes all mappings
clear() - Method in class weka.core.xml.XMLBasicSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLDocument: sets up an empty DOM document, with the current DOCTYPE and root node.
clear() - Method in class weka.core.xml.XMLSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLSerializationMethodHandler: removes all current methods and adds the methods according to the
clear() - Method in class weka.experiment.ResultMatrix: removes the stored data and the ordering, but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixCSV: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixGnuPlot: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixLatex: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.xml.XMLExperiment: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.beans.xml.XMLBeans: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.GenericObjectEditorHistory: Clears the history.
clear() - Method in class weka.gui.LogWindow: clears the output
clear() - Method in class weka.gui.sql.ConnectionPanel: sets the parameters back to standard.
clear() - Method in class weka.gui.sql.InfoPanel: clears the content of the panel
clear() - Method in class weka.gui.sql.QueryPanel: clears the textarea.
clear() - Method in class weka.gui.sql.ResultPanel: sets the parameters back to standard
clear() - Method in class weka.gui.sql.SqlViewer: calls the clear method of all sub-panels to set back to default values and free up memory.
clearAttributeSpecs() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Clear the list of attribute specifications
clearCache() - Static method in class weka.core.ClassDiscovery: clears the cache for class/classnames queries.
clearClassCache() - Static method in class weka.core.ClassDiscovery: Calls clearCache() and resets the cache of classes on the classpath (i.e.
clearHeader() - Method in class weka.experiment.ResultMatrix: removes all the header information.
clearLayout() - Method in class weka.gui.beans.KnowledgeFlowApp
clearRanking() - Method in class weka.experiment.ResultMatrix: clears the currently stored ranking data.
clearRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle with the background color.
clearResults() - Method in class weka.gui.ResultHistoryPanel: Removes all of the result buffers from the history.
clearSearch() - Method in class weka.gui.arffviewer.ArffPanel: clears the search, i.e.
clearSearch() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: clears the search, i.e.
clearStatus() - Method in class weka.gui.beans.LogPanel: Clear the status area.
clearSummary() - Method in class weka.experiment.ResultMatrix: clears the current summary data.
clearUndo() - Method in interface weka.core.Undoable: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffPanel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableModel: removes the undo history
clearUndoStack() - Method in class weka.classifiers.bayes.net.EditableBayesNet: remove all actions from the undo stack
clip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
clipRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
clone() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Creates and returns a clone of this object.
clone() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Allows to clone a model (shallow copy).
clone() - Method in class weka.classifiers.trees.j48.Distribution: Clones distribution (Deep copy of distribution).
clone() - Method in class weka.core.AlgVector: Creates and returns a clone of this object.
clone() - Method in class weka.core.Capabilities: Creates and returns a copy of this object.
clone() - Method in class weka.core.Matrix: Deprecated. Creates and returns a clone of this object.
clone() - Method in class weka.core.matrix.DoubleVector: Clones the DoubleVector object.
clone() - Method in class weka.core.matrix.IntVector: Clones the IntVector object.
clone() - Method in class weka.core.matrix.Matrix: Clone the Matrix object.
clone() - Method in class weka.core.PropertyPath.PathElement: returns a clone of the current object
clone() - Method in class weka.core.TestInstances: creates a clone of the current object
clone() - Method in class weka.core.Trie: returns a deep copy of itself
clone() - Method in class weka.core.Trie.TrieNode: creates a deep copy of itself
clone(Estimator) - Static method in class weka.estimators.Estimator: Creates a deep copy of the given estimator using serialization.
clone() - Method in class weka.estimators.MultivariateGaussianEstimator
close(ResultSet) - Method in class weka.experiment.DatabaseUtils: closes the ResultSet and the statement that generated the ResultSet to avoid memory leaks in JDBC drivers - in contrast to the JDBC specs, a lot of JDBC drives don't clean up correctly.
close() - Method in class weka.experiment.DatabaseUtils: closes the m_PreparedStatement to avoid memory leaks.
close() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
close() - Method in class weka.gui.LogWindow: closes the frame
closeAllFiles() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes all open files
closeAllTabs() - Method in class weka.gui.beans.KnowledgeFlowApp
closeFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFile(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFrame() - Method in class weka.gui.SetInstancesPanel: closes the frame, i.e., the visibility is set to false.
closestPoint(Instance, Instances, int[]) - Method in class weka.core.EuclideanDistance: Returns the index of the closest point to the current instance.
closeToDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToToleranceTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closingCancel() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under a CANCEL condition
closingCancel() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the Cancel button
closingCancel() - Method in class weka.gui.PropertySheetPanel: Pass on a CANCEL closing notificiation to the customizer (if one is in use).
closingOK() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under an OK condition
closingOK() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the OK button.
closingOK() - Method in class weka.gui.PropertySheetPanel: Pass on an OK closing notification to the customizer (if one is in use)
Cluster - Class in weka.core.pmml.jaxbbindings: Java class for Cluster element declaration.
Cluster() - Constructor for class weka.core.pmml.jaxbbindings.Cluster
ClusterDefinition - Class in weka.datagenerators: Ancestor to all ClusterDefinitions, i.e., subclasses that handle their own parameters that the cluster generator only passes on.
ClusterDefinition() - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster, without a parent cluster (necessary for GOE)
ClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster
clusterDefinitionsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
Clusterer - Interface in weka.clusterers: Interface for clusterers.
Clusterer - Class in weka.gui.beans: Bean that wraps around weka.clusterers
Clusterer() - Constructor for class weka.gui.beans.Clusterer: Creates a new Clusterer instance.
ClustererAssignmentsPlotInstances - Class in weka.gui.explorer: A class for generating plottable cluster assignments.
ClustererAssignmentsPlotInstances() - Constructor for class weka.gui.explorer.ClustererAssignmentsPlotInstances
ClustererBeanInfo - Class in weka.gui.beans: BeanInfo class for the Clusterer wrapper bean
ClustererBeanInfo() - Constructor for class weka.gui.beans.ClustererBeanInfo
ClustererCustomizer - Class in weka.gui.beans: GUI customizer for the Clusterer wrapper bean
ClustererCustomizer() - Constructor for class weka.gui.beans.ClustererCustomizer
ClustererPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
ClustererPanel() - Constructor for class weka.gui.explorer.ClustererPanel: Creates the clusterer panel
ClustererPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Clusterer panel and execute it.
ClustererPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluator
ClustererPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the clusterer performance evaluator
ClustererPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
clustererTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the tip text for this property
clustererTipText() - Method in class weka.clusterers.SingleClustererEnhancer: Returns the tip text for this property
clustererTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the tip text for this property
clustererTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the tip text for this property.
ClusterEvaluation - Class in weka.clusterers: Class for evaluating clustering models.
ClusterEvaluation() - Constructor for class weka.clusterers.ClusterEvaluation: Constructor.
ClusterGenerator - Class in weka.datagenerators: Abstract class for cluster data generators.
ClusterGenerator() - Constructor for class weka.datagenerators.ClusterGenerator: initializes the generator
ClusteringField - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringField element declaration.
ClusteringField() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringField
ClusteringModel - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModel element declaration.
ClusteringModel() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModel
ClusteringModelQuality - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModelQuality element declaration.
ClusteringModelQuality() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModelQuality
clusterInstance(Instance) - Method in class weka.clusterers.AbstractClusterer: Classifies a given instance.
clusterInstance(Instance) - Method in interface weka.clusterers.Clusterer: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.Cobweb: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.FarthestFirst: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
clusterInstance(Instance) - Method in class weka.clusterers.SimpleKMeans: Classifies a given instance.
ClusterMembership - Class in weka.filters.unsupervised.attribute: A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
ClusterMembership() - Constructor for class weka.filters.unsupervised.attribute.ClusterMembership
clusterPriors() - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in interface weka.clusterers.DensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in class weka.clusterers.EM: Returns the cluster priors.
clusterPriors() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the cluster priors.
clusterResultsToString() - Method in class weka.clusterers.ClusterEvaluation: return the results of clustering.
clusterSubTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
clusterTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
Cobweb - Class in weka.clusterers: Class implementing the Cobweb and Classit clustering algorithms.

Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.
Cobweb() - Constructor for class weka.clusterers.Cobweb: default constructor
Cobweb.CNode - Class in weka.clusterers: Inner class handling node operations for Cobweb.
Cobweb.CNode(int) - Constructor for class weka.clusterers.Cobweb.CNode: Creates an empty CNode instance.
Cobweb.CNode(int, Instance) - Constructor for class weka.clusterers.Cobweb.CNode: Creates a new leaf CNode instance.
cochransCriterion(double[][]) - Static method in class weka.core.ContingencyTables: Tests if Cochran's criterion is fullfilled for the given contingency table.
codingCost() - Method in class weka.classifiers.trees.j48.C45Split: Returns coding cost for split (used in rule learner).
codingCost() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns coding costs of model.
Coefficient - Class in weka.core.pmml.jaxbbindings: Java class for Coefficient element declaration.
Coefficient() - Constructor for class weka.core.pmml.jaxbbindings.Coefficient
coefficients() - Method in class weka.classifiers.functions.LinearRegression: Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.functions.Logistic: Returns the coefficients for this logistic model.
coefficients() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Return the array of coefficients
Coefficients - Class in weka.core.pmml.jaxbbindings: Java class for Coefficients element declaration.
Coefficients() - Constructor for class weka.core.pmml.jaxbbindings.Coefficients
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Collapses a tree to a node if training error doesn't increase.
collapseTreeTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
colNameWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
COLON - Static variable in interface weka.core.json.sym
COLOR_STDERR - Static variable in class weka.gui.LogWindow: the Color of the style for stderr
COLOR_STDOUT - Static variable in class weka.gui.LogWindow: the color of the style for stdout
Colors - Class in weka.gui.treevisualizer: This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
Colors() - Constructor for class weka.gui.treevisualizer.Colors
combinationRuleTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
combinedDL(double, double) - Method in class weka.classifiers.rules.RuleStats: Compute the combined DL of the ruleset in this class, i.e.
combSort11(double[], int[]) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch: sorts the two given arrays.
COMMA - Static variable in interface weka.core.json.sym
COMMA - Static variable in interface weka.core.mathematicalexpression.sym
COMMA - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
CommandlineRunnable - Interface in weka.core: Interface to something that can be run from the command line.
compactify() - Method in class weka.core.Instances: Compactifies the set of instances.
compare(String, String) - Method in class weka.core.ClassDiscovery.StringCompare: Compares its two arguments for order.
compare(Instance, Instance) - Method in class weka.core.InstanceComparator: compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
COMPAREFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for COMPARE-FUNCTION.
compareTo(AssociationRule) - Method in class weka.associations.AssociationRule: Compare this rule to the supplied rule.
compareTo(Item) - Method in class weka.associations.Item: Ensures that items will be sorted in descending order of frequency.
compareTo(SplitCandidate) - Method in class weka.classifiers.trees.ht.SplitCandidate
compareTo(AttributeLocator) - Method in class weka.core.AttributeLocator: Compares this object with the specified object for order.
compareTo(String) - Method in class weka.core.Version: checks the version of this class against the given version-string
compareTo(SortedTableModel.SortContainer) - Method in class weka.gui.SortedTableModel.SortContainer: Compares this object with the specified object for order.
ComparisonMeasure - Class in weka.core.pmml.jaxbbindings: Java class for ComparisonMeasure element declaration.
ComparisonMeasure() - Constructor for class weka.core.pmml.jaxbbindings.ComparisonMeasure
Comparisons - Class in weka.core.pmml.jaxbbindings: Java class for Comparisons element declaration.
Comparisons() - Constructor for class weka.core.pmml.jaxbbindings.Comparisons
ComponentHelper - Class in weka.gui: A helper class for some common tasks with Dialogs, Icons, etc.
ComponentHelper() - Constructor for class weka.gui.ComponentHelper
componentHidden(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentMoved(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentResized(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentShown(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
CompoundPredicate - Class in weka.core.pmml.jaxbbindings: Java class for CompoundPredicate element declaration.
CompoundPredicate() - Constructor for class weka.core.pmml.jaxbbindings.CompoundPredicate
CompoundRule - Class in weka.core.pmml.jaxbbindings: Java class for CompoundRule element declaration.
CompoundRule() - Constructor for class weka.core.pmml.jaxbbindings.CompoundRule
compressOutputTipText() - Method in class weka.core.converters.ArffSaver: Returns the tip text for this property
compressOutputTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
compressOutputTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
Compute - Interface in weka.experiment: Interface to something that can accept remote connections and execute a task.
computeMinMaxAtts() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set up the bounds of our graphic based by finding the smallest reasonable area in the instance space to surround our data points.
Con1 - Class in weka.core.pmml.jaxbbindings: Java class for Con element declaration.
Con1() - Constructor for class weka.core.pmml.jaxbbindings.Con1
cond() - Method in class weka.core.matrix.Matrix: Matrix condition (2 norm)
cond() - Method in class weka.core.matrix.SingularValueDecomposition: Two norm condition number
ConditionalDensityEstimator - Interface in weka.classifiers: Interface for numeric prediction schemes that can output conditional density estimates.
ConditionalEstimator - Interface in weka.estimators: Interface for conditional probability estimators.
ConditionalSufficientStats - Class in weka.classifiers.trees.ht: Records sufficient stats for an attribute
ConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.ConditionalSufficientStats
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.Split: Returns the condition for the supplied branch name
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
confidenceFactorTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
confidenceForRule(AprioriItemSet, AprioriItemSet) - Static method in class weka.associations.AprioriItemSet: Outputs the confidence for a rule.
CONFIG - Static variable in class weka.core.Debug: the log level Vonfig
ConfigurationEvent - Class in weka.gui.beans: Matching event for ConfigurationListener.
ConfigurationEvent(Object) - Constructor for class weka.gui.beans.ConfigurationEvent
ConfigurationListener - Interface in weka.gui.beans: Matching listener for ConfigurationEvent.
ConfigurationProducer - Interface in weka.gui.beans: Marker interface for components that can share their configuration.
ConfusionMatrix - Class in weka.classifiers.evaluation: Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
confusionMatrix() - Method in class weka.classifiers.Evaluation: Returns a copy of the confusion matrix.
ConfusionMatrix(String[]) - Constructor for class weka.classifiers.evaluation.ConfusionMatrix: Creates the confusion matrix with the given class names.
confusionMatrix() - Method in class weka.classifiers.evaluation.Evaluation: Returns a copy of the confusion matrix.
ConfusionMatrix - Class in weka.core.pmml.jaxbbindings: Java class for ConfusionMatrix element declaration.
ConfusionMatrix() - Constructor for class weka.core.pmml.jaxbbindings.ConfusionMatrix
ConjugateGradientOptimization - Class in weka.core: This subclass of Optimization.java implements conjugate gradient descent rather than BFGS updates, by overriding findArgmin(), with the same tests for convergence, and applies the same line search code.
ConjugateGradientOptimization() - Constructor for class weka.core.ConjugateGradientOptimization: Constructor that sets MAXITS to 2000 by default and the parameter in the second weak Wolfe condition to 0.1.
connect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection: Connects two units together.
CONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent: it was a connect try
CONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This flag is set once the unit has a connection.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection with respect to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(String) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(String) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(String) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(String) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.MetaBean
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied event name.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextSaver
connectionAllowed(String) - Method in class weka.gui.beans.TextSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the named event
connectionChange(ConnectionEvent) - Method in interface weka.gui.sql.event.ConnectionListener: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.QueryPanel: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when the connection is either established or disconnected.
ConnectionEvent - Class in weka.gui.sql.event: An event that is generated when a connection is established or dropped.
ConnectionEvent(Object, int, DbUtils) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionEvent(Object, int, DbUtils, Exception) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionListener - Interface in weka.gui.sql.event: A listener for connect/disconnect events.
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Appender: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Associator: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Classifier: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.CrossValidationFoldMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.DataVisualizer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Filter: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.FlowByExpression
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageViewer
connectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.Join: Deals with a new connection
connectionNotification(String, Object) - Method in class weka.gui.beans.Loader: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean: Notify this object that it has been registered as a listener with a source with respect to the named event.
connectionNotification(String, Object) - Method in class weka.gui.beans.ModelPerformanceChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.Sorter: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.StripChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringLabeler: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringReplacer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TextSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TrainTestSplitMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
ConnectionNotificationConsumer - Interface in weka.gui.beans: Interface for Beans that can receive (dis-)connection events generated when (dis-)connecting data processing nodes in the Weka KnowledgeFlow.
ConnectionPanel - Class in weka.gui.sql: Enables the user to insert a database URL, plus user/password to connect to this database.
ConnectionPanel(JFrame) - Constructor for class weka.gui.sql.ConnectionPanel: initializes the panel.
connectToDatabase() - Method in class weka.core.converters.DatabaseLoader: Opens a connection to the database
connectToDatabase() - Method in class weka.core.converters.DatabaseSaver: Opens a connection to the database.
connectToDatabase() - Method in class weka.experiment.DatabaseUtils: Opens a connection to the database.
ConsequentSequence - Class in weka.core.pmml.jaxbbindings: Java class for ConsequentSequence element declaration.
ConsequentSequence() - Constructor for class weka.core.pmml.jaxbbindings.ConsequentSequence
conservativeForwardSelectionTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
ConsoleLogger - Class in weka.core.logging: A simple logger that outputs the logging information in the console.
ConsoleLogger() - Constructor for class weka.core.logging.ConsoleLogger
CONST - Static variable in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateKernelEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateNormalEstimator: Constant for Gaussian density
CONST_AUTOMATIC_SHAPE - Static variable in class weka.gui.visualize.Plot2D
CONSTANT - Static variable in class weka.classifiers.lazy.LWL
Constant - Class in weka.core.pmml: Class encapsulating a Constant Expression.
Constant(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Constant: Construct an new Constant Expression.
Constant - Class in weka.core.pmml.jaxbbindings: Java class for Constant element declaration.
Constant() - Constructor for class weka.core.pmml.jaxbbindings.Constant
Constraints - Class in weka.core.pmml.jaxbbindings: Java class for Constraints element declaration.
Constraints() - Constructor for class weka.core.pmml.jaxbbindings.Constraints
constructMappedInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
constructWithCopy(double[][]) - Static method in class weka.core.matrix.Matrix: Construct a matrix from a copy of a 2-D array.
containChildBallsTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the tip text for this property.
containedBy(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
containedByTreatZeroAsMissing(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
contains(int) - Method in class weka.classifiers.bayes.net.ParentSet: test if node is contained in parent set
contains(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Checks whether an element is in the set.
contains(String) - Method in class weka.core.pmml.Array: Returns true if the array contains this string value.
contains(int) - Method in class weka.core.pmml.Array: Returns true if the array contains this integer value.
contains(double) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(float) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(PrintStream) - Method in class weka.core.Tee: checks whether the given PrintStream is already in the list.
contains(Object) - Method in class weka.core.Trie: Returns true if this collection contains the specified element.
contains(String) - Method in class weka.core.Trie.TrieNode: checks whether a suffix can be found in its children
contains(String) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given property
contains(Class<?>) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given class
contains(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Tests whether the specified object is a component in this list.
contains(String) - Method in class weka.gui.HierarchyPropertyParser: Whether the HierarchyPropertyParser contains the given string
containsAll(Collection<?>) - Method in class weka.core.Trie: Returns true if this collection contains all of the elements in the specified collection.
containsEnvVariables(String) - Static method in class weka.core.Environment: Tests for the presence of environment variables.
containsItems(ArrayList<Item>, boolean) - Method in class weka.associations.AssociationRule
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Tests if the specified double is a key in this hashtable.
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache: Checks if the specified key maps with an entry in the cache table
containsPrefix(String) - Method in class weka.core.Trie: checks whether the given prefix is stored in the trie
containsValue(double) - Method in class weka.core.pmml.FieldMetaInfo.Interval: Returns true if this interval contains the supplied value.
containsWindow(Class<?>) - Method in class weka.gui.Main: checks, whether an instance of the given window class is already in the Window list.
containsWindow(String) - Method in class weka.gui.Main: checks, whether a window with the given title is already in the Window list.
context() - Method in class weka.gui.HierarchyPropertyParser: The context of the current node, i.e.
ContingencyTables - Class in weka.core: Class implementing some statistical routines for contingency tables.
ContingencyTables() - Constructor for class weka.core.ContingencyTables
CONTINUOUS - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster subtype: continuous
CONTSCORINGMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for CONT-SCORING-METHOD.
ContStats - Class in weka.core.pmml.jaxbbindings: Java class for ContStats element declaration.
ContStats() - Constructor for class weka.core.pmml.jaxbbindings.ContStats
ConverterFileChooser - Class in weka.gui: A specialized JFileChooser that lists all available file Loaders and Savers.
ConverterFileChooser() - Constructor for class weka.gui.ConverterFileChooser: onstructs a FileChooser pointing to the user's default directory.
ConverterFileChooser(File) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given File as the path.
ConverterFileChooser(String) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given path.
ConverterUtils - Class in weka.core.converters: Utility routines for the converter package.
ConverterUtils() - Constructor for class weka.core.converters.ConverterUtils
ConverterUtils.DataSink - Class in weka.core.converters: Helper class for saving data to files.
ConverterUtils.DataSink(String) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data to the given file.
ConverterUtils.DataSink(Saver) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data to the given Saver (expected to be fully configured).
ConverterUtils.DataSink(OutputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data in the stream (always in ARFF format).
ConverterUtils.DataSource - Class in weka.core.converters: Helper class for loading data from files and URLs.
ConverterUtils.DataSource(String) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Tries to load the data from the file.
ConverterUtils.DataSource(Instances) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given dataset.
ConverterUtils.DataSource(Loader) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given Loader.
ConverterUtils.DataSource(InputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given input stream.
convertInfixToPostfix(String) - Method in class weka.core.AttributeExpression: Converts a string containing a mathematical expression in infix form to postfix form.
convertInstance(Instance) - Method in interface weka.attributeSelection.AttributeTransformer: Transforms an instance in the format of the original data to the transformed space
convertInstance(Instance) - Method in class weka.attributeSelection.PrincipalComponents: Transform an instance in original (unormalized) format.
convertNewLines(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
convertNominalTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
convertNumericAttToNominal(int, ArrayList<String>) - Method in class weka.core.pmml.MiningSchema: Convert a numeric attribute in the mining schema to nominal.
convertStringAttsToNominal() - Method in class weka.core.pmml.MiningSchema: Method to convert any string attributes in the mining schema Instances to nominal attributes.
convertToAttribX(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw y value to Panel y coordinate.
convertToRelativePath(File) - Static method in class weka.core.Utils: Converts a File's absolute path to a path relative to the user (ie start) directory.
convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet: Outputs the conviction for a rule.
copy(ParentSet) - Method in class weka.classifiers.bayes.net.ParentSet: Copy makes current parents set equal to other parent set
copy() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Return a shallow copy of this kernel
copy() - Method in class weka.classifiers.rules.JRip.Antd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NominalAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NumericAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.RipperRule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.rules.Rule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Makes a copy of this CorrelationSplitInfo object
copy() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: makes a copy of the SplitEvaluate object
copy() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Makes a copy of this SplitInfo object
copy() - Method in class weka.core.Attribute: Produces a shallow copy of this attribute.
copy(String) - Method in class weka.core.Attribute: Produces a shallow copy of this attribute with a new name.
copy() - Method in class weka.core.BinarySparseInstance: Produces a shallow copy of this instance.
copy() - Method in interface weka.core.Copyable: This method produces a shallow copy of an object.
copy() - Method in class weka.core.DenseInstance: Produces a shallow copy of this instance.
copy() - Method in class weka.core.FastVector: Deprecated. Produces a shallow copy of this vector.
copy() - Method in class weka.core.matrix.DoubleVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.IntVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.Matrix: Make a deep copy of a matrix
copy() - Method in class weka.core.SparseInstance: Produces a shallow copy of this instance.
Copy - Class in weka.filters.unsupervised.attribute: An instance filter that copies a range of attributes in the dataset.
Copy() - Constructor for class weka.filters.unsupervised.attribute.Copy
copy(File, File) - Static method in class weka.gui.scripting.ScriptUtils: Copies the file/directory (recursively).
Copyable - Interface in weka.core: Interface implemented by classes that can produce "shallow" copies of their objects.
copyArea(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
copyContent() - Method in class weka.gui.arffviewer.ArffPanel: copies the content of the selection to the clipboard
copyContent() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: copies the content of the selection to the clipboard
copyElements() - Method in class weka.core.FastVector: Deprecated. Clones the vector and shallow copies all its elements.
copyInto(Object[]) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Copies the components of this list into the specified array.
copyRelationalValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Copies relational values contained in the instance copied to a new dataset.
copyRelationalValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Takes relational values referenced by an Instance and copies them from a source dataset to a destination dataset.
Copyright - Class in weka.core: A class for providing centralized Copyright information.
Copyright() - Constructor for class weka.core.Copyright
copyStringValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Copies string values contained in the instance copied to a new dataset.
copyStringValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Takes string values referenced by an Instance and copies them from a source dataset to a destination dataset.
copyToBuffer(Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp: Utility routine that serializes the supplied Vector of BeanInstances to XML
copyToClipboard() - Method in class weka.gui.sql.InfoPanel: copies the currently selected error message to the clipboard
CORE_FILE_LOADERS - Static variable in class weka.core.converters.ConverterUtils: the core loaders - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
CORE_FILE_SAVERS - Static variable in class weka.core.converters.ConverterUtils: the core savers - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
correct() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of correct classifications (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlation(double[], double[], int) - Static method in class weka.core.Utils: Returns the correlation coefficient of two double vectors.
correlation - Variable in class weka.experiment.PairedStats: The correlation coefficient
CorrelationAttributeEval - Class in weka.attributeSelection: CorrelationAttributeEval :

Evaluates the worth of an attribute by measuring the correlation (Pearson's) between it and the class.

Nominal attributes are considered on a value by value basis by treating each value as an indicator.
CorrelationAttributeEval() - Constructor for class weka.attributeSelection.CorrelationAttributeEval
correlationCoefficient() - Method in class weka.classifiers.Evaluation: Returns the correlation coefficient if the class is numeric.
correlationCoefficient() - Method in class weka.classifiers.evaluation.Evaluation: Returns the correlation coefficient if the class is numeric.
CorrelationFields - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationFields element declaration.
CorrelationFields() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationFields
CorrelationMethods - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationMethods element declaration.
CorrelationMethods() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationMethods
Correlations - Class in weka.core.pmml.jaxbbindings: Java class for Correlations element declaration.
Correlations() - Constructor for class weka.core.pmml.jaxbbindings.Correlations
CorrelationSplitInfo - Class in weka.classifiers.trees.m5: Finds split points using correlation.
CorrelationSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo: Constructs an object which contains the split information
CorrelationValues - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationValues element declaration.
CorrelationValues() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationValues
COS - Static variable in interface weka.core.mathematicalexpression.sym
COS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
CostBenefitAnalysis - Class in weka.gui.beans: Bean that aids in analyzing cost/benefit tradeoffs.
CostBenefitAnalysis() - Constructor for class weka.gui.beans.CostBenefitAnalysis: Constructor.
CostBenefitAnalysisBeanInfo - Class in weka.gui.beans: Bean info class for the cost/benefit analysis
CostBenefitAnalysisBeanInfo() - Constructor for class weka.gui.beans.CostBenefitAnalysisBeanInfo
CostCurve - Class in weka.classifiers.evaluation: Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
CostCurve() - Constructor for class weka.classifiers.evaluation.CostCurve
CostMatrix - Class in weka.classifiers: Class for storing and manipulating a misclassification cost matrix.
CostMatrix(int) - Constructor for class weka.classifiers.CostMatrix: Creates a default cost matrix of a particular size.
CostMatrix(CostMatrix) - Constructor for class weka.classifiers.CostMatrix: Creates a cost matrix that is a copy of another.
CostMatrix(Reader) - Constructor for class weka.classifiers.CostMatrix: Reads a matrix from a reader.
CostMatrixEditor - Class in weka.gui: Class for editing CostMatrix objects.
CostMatrixEditor() - Constructor for class weka.gui.CostMatrixEditor: Constructs a new CostMatrixEditor.
costMatrixSourceTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
CostSensitiveClassifier - Class in weka.classifiers.meta: A metaclassifier that makes its base classifier cost-sensitive.
CostSensitiveClassifier() - Constructor for class weka.classifiers.meta.CostSensitiveClassifier: Default constructor.
CostSensitiveClassifierSplitEvaluator - Class in weka.experiment: SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
CostSensitiveClassifierSplitEvaluator() - Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
count - Variable in class weka.experiment.PairedStats: The number of data points seen
count - Variable in class weka.experiment.Stats: The number of values seen
countData() - Method in class weka.classifiers.rules.RuleStats: Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
countData(int, Instances, double[][]) - Method in class weka.classifiers.rules.RuleStats: Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed.
counter() - Method in class weka.associations.ItemSet: Gets the counter
Counts - Class in weka.core.pmml.jaxbbindings: Java class for Counts element declaration.
Counts() - Constructor for class weka.core.pmml.jaxbbindings.Counts
countsForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet: Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
COUNTTABLETYPE - Class in weka.core.pmml.jaxbbindings: Java class for COUNT-TABLE-TYPE complex type.
COUNTTABLETYPE() - Constructor for class weka.core.pmml.jaxbbindings.COUNTTABLETYPE
countWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
covariance(double[][], double[]) - Static method in class weka.estimators.MultivariateGaussianEstimator: Calculates the covariance matrix of a sample matrix.
Covariances - Class in weka.core.pmml.jaxbbindings: Java class for Covariances element declaration.
Covariances() - Constructor for class weka.core.pmml.jaxbbindings.Covariances
CovariateList - Class in weka.core.pmml.jaxbbindings: Java class for CovariateList element declaration.
CovariateList() - Constructor for class weka.core.pmml.jaxbbindings.CovariateList
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
covers(Instance) - Method in class weka.classifiers.rules.JRip.Antd
covers(Instance) - Method in class weka.classifiers.rules.JRip.NominalAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.NumericAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.RipperRule: Whether the instance covered by this rule
covers(Instance) - Method in class weka.classifiers.rules.Rule: Whether the instance covered by this rule
CoverTree - Class in weka.core.neighboursearch: Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.

For more information and original source code see:

Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor.
CoverTree() - Constructor for class weka.core.neighboursearch.CoverTree: default constructor.
CoverTree.CoverTreeNode - Class in weka.core.neighboursearch: class representing a node of the cover tree.
CoverTree.CoverTreeNode() - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor for the class.
CoverTree.CoverTreeNode(Integer, double, double, Stack<CoverTree.CoverTreeNode>, int, int) - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor.
CramersV(double[][]) - Static method in class weka.core.ContingencyTables: Computes Cramer's V for a contingency table.
create(List<Object>, List<Integer>) - Static method in class weka.core.pmml.Array
create(Element) - Static method in class weka.core.pmml.Array: Static factory method for creating non-sparse or sparse array types as needed.
create(Reader) - Method in class weka.gui.treevisualizer.TreeBuild: This will build A node structure from the dotty format passed.
create() - Method in class weka.gui.visualize.PostscriptGraphics: Clone a PostscriptGraphics object
createAggregate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Aggregate
createAlternate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Alternate
createAnnotation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Annotation
createAnova() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Anova
createAnovaRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnovaRow
createAntecedentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AntecedentSequence
createAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnyDistribution
createApplication() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Application
createApply() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Apply
createARIMA(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<ArrayType>}
createArrayType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ArrayType
createAssociationModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationModel
createAssociationRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationRule
createAttribute() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Attribute
createBaseCumHazardTables() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaseCumHazardTables
createBaseline() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Baseline
createBaselineCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineCell
createBaselineModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineModel
createBaselineStratum() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineStratum
createBayesInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInput
createBayesInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInputs
createBayesOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesOutput
createBinarySimilarity() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BinarySimilarity
createBoundaryValueMeans() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValueMeans
createBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValues
createCategoricalPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CategoricalPredictor
createCategories() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Categories
createCategory() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Category
createCharacteristic() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristic
createCharacteristics() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristics
createChebychev() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Chebychev
createChildParent() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ChildParent
createCityBlock() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CityBlock
createClassLabels() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClassLabels
createCluster() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Cluster
createClusteringField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringField
createClusteringModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModel
createClusteringModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModelQuality
createCoefficient() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficient
createCoefficients() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficients
createComparisonMeasure() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ComparisonMeasure
createComparisons() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Comparisons
createCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundPredicate
createCompoundRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundRule
createCon() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Con1
createConfusionMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConfusionMatrix
createConsequentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConsequentSequence
createConstant() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constant
createConstraints() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constraints
createContStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ContStats
createCorrelationFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationFields
createCorrelationMethods() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationMethods
createCorrelations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Correlations
createCorrelationValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationValues
createCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Counts
createCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createCOUNTTABLETYPE() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of COUNTTABLETYPE
createCovariances() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Covariances
createCovariateList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CovariateList
createDataDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataDictionary
createDataField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataField
createDecision() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decision
createDecisions() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decisions
createDecisionTree() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DecisionTree
createDefineFunction() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DefineFunction
createDelimiter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Delimiter
createDerivedField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DerivedField
createDiscretize() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Discretize
createDiscretizeBin() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscretizeBin
createDiscrStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscrStats
createDocumentTermMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DocumentTermMatrix
createEuclidean() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Euclidean
createEventValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of EventValues
createExperimentIndex() - Method in class weka.experiment.DatabaseUtils: Attempts to create the experiment index table.
createExperimentIndexEntry(ResultProducer) - Method in class weka.experiment.DatabaseUtils: Attempts to insert a results entry for the table into the experiment index.
createExponentialSmoothing() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ExponentialSmoothing
createExtension() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Extension
createFactorList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FactorList
createFalse() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of False
createFieldColumnPair() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldColumnPair
createFieldRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldRef
createFieldValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValue
createFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValueCount
createGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GaussianDistribution
createGeneralRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GeneralRegressionModel
createHeader() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Header
createIndices(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInlineTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InlineTable
createInstanceField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceField
createInstanceFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceFields
createINTEntries(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInterval() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Interval
createINTSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of INTSparseArray
createItem() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Item
createItemRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ItemRef
createItemset() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Itemset
createJaccard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Jaccard
createKNNInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInput
createKNNInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInputs
createKohonenMap() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KohonenMap
createLevel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Level
createLiftData() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftData
createLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftGraph
createLinearKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearKernelType
createLinearNorm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearNorm
createLink(String, String) - Static method in class weka.gui.BrowserHelper: Generates a label with a clickable link.
createLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LocalTransformations
createMapValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MapValues
createMatCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MatCell
createMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Matrix
createMiningBuildTask() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningBuildTask
createMiningField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningField
createMiningModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningModel
createMiningSchema() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningSchema
createMinkowski() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Minkowski
createMissingValueWeights() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MissingValueWeights
createModelExplanation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelExplanation
createModelLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelLiftGraph
createModelStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelStats
createModelVerification() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelVerification
createMultivariateStat() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStat
createMultivariateStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStats
createNaiveBayesModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NaiveBayesModel
createNearestNeighborModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NearestNeighborModel
createNeuralInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInput
createNeuralInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInputs
createNeuralLayer() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralLayer
createNeuralNetwork() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralNetwork
createNeuralOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutput
createNeuralOutputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutputs
createNeuron() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Neuron
createNewVisualizerWindow(Classifier, Instances) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new GUI window with all of the BoundaryVisualizer trappings,
createNode() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Node
createNormalizedCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createNormContinuous() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormContinuous
createNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormDiscrete
createNumericInfo() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericInfo
createNumericPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericPredictor
createOptimumLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OptimumLiftGraph
createOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Output
createOutputField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OutputField
createPairCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PairCounts
createParameter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Parameter
createParameterField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterField
createParameterList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterList
createParamMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParamMatrix
createPartition() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Partition
createPartitionFieldStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PartitionFieldStats
createPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCell
createPCovCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovCell
createPCovMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovMatrix
createPMML() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PMML
createPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PoissonDistribution
createPolynomialKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PolynomialKernelType
createPPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPCell
createPPMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPMatrix
createPredictiveModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictiveModelQuality
createPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Predictor
createPredictorTerm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictorTerm
createQuantile() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Quantile
createRadialBasisKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RadialBasisKernelType
createRandomLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RandomLiftGraph
createREALEntries(List<Double>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Double>>}
createREALSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of REALSparseArray
createRegression() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Regression
createRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionModel
createRegressionTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionTable
createResultField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ResultField
createResultsTable(ResultProducer, String) - Method in class weka.experiment.DatabaseUtils: Creates a results table for the supplied result producer.
createROC() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROC
createROCGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROCGraph
createRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Row
createRuleSelectionMethod() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSelectionMethod
createRuleSet() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSet
createRuleSetModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSetModel
createScorecard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Scorecard
createScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ScoreDistribution
createSeasonalityExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SeasonalityExpoSmooth
createSeasonalTrendDecomposition(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createSegment() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segment
createSegmentation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segmentation
createSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Sequence
createSequenceModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceModel
createSequenceReference() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceReference
createSequenceRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceRule
createSetPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SetPredicate
createSetReference() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SetReference
createSigmoidKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SigmoidKernelType
createSimpleMatching() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleMatching
createSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimplePredicate
createSimpleRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleRule
createSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleSetPredicate
createSingleton(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp: Create the singleton instance of the KnowledgeFlow
createSingleton() - Static method in class weka.gui.GUIChooser: Create a singleton instance of the GUIChooser
createSingleton(String[]) - Static method in class weka.gui.Main: Create the singleton instance of the Main GUI.
createSpectralAnalysis(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createSquaredEuclidean() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SquaredEuclidean
createSubsampleWithoutReplacement(Random, int, int, int, int[]) - Method in class weka.filters.supervised.instance.Resample: creates the subsample without replacement.
createSubsampleWithoutReplacement(Random, int, int) - Method in class weka.filters.unsupervised.instance.Resample: creates the subsample without replacement
createSubsampleWithReplacement(Random, int, int, int, int[]) - Method in class weka.filters.supervised.instance.Resample: creates the subsample with replacement.
createSubsampleWithReplacement(Random, int, int) - Method in class weka.filters.unsupervised.instance.Resample: creates the subsample with replacement
createSupportVector() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVector
createSupportVectorMachine() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectorMachine
createSupportVectorMachineModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectorMachineModel
createSupportVectors() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectors
createTableLocator() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TableLocator
createTanimoto() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Tanimoto
createTarget() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Target
createTargets() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Targets
createTargetValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValue
createTargetValueCount() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValueCount
createTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValueCounts
createTaxonomy() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Taxonomy
createTestDistributions() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TestDistributions
createTextCorpus() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextCorpus
createTextDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextDictionary
createTextDocument() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextDocument
createTextModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModel
createTextModelNormalization() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModelNormalization
createTextModelSimiliarity() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModelSimiliarity
createTime() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Time
createTimeAnchor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeAnchor
createTimeCycle() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeCycle
createTimeException() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeException
createTimeSeries() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeSeries
createTimeSeriesModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeSeriesModel
createTimestamp() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Timestamp
createTimeValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeValue
createTrainingInstances() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TrainingInstances
createTransformationDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TransformationDictionary
createTreeModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TreeModel
createTrendExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TrendExpoSmooth
createTrue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of True
createUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of UniformDistribution
createUnivariateStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of UnivariateStats
createValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Value
createVectorDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorDictionary
createVectorFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorFields
createVectorInstance() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorInstance
createVerificationField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VerificationField
createVerificationFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VerificationFields
createXCoordinates() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of XCoordinates
createYCoordinates() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of YCoordinates
crossValidate(NaiveBayesUpdateable, Instances, Random) - Static method in class weka.classifiers.trees.j48.NBTreeNoSplit: Utility method for fast 5-fold cross validation of a naive bayes model
CrossValidateAttributes() - Method in class weka.attributeSelection.AttributeSelection: Perform a cross validation for attribute selection.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.evaluation.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.evaluation.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(DensityBasedClusterer, Instances, int, Random) - Static method in class weka.clusterers.ClusterEvaluation: Perform a cross-validation for DensityBasedClusterer on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Static method in class weka.clusterers.ClusterEvaluation: Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances.
crossValidateTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
CrossValidationFoldMaker - Class in weka.gui.beans: Bean for splitting instances into training ant test sets according to a cross validation
CrossValidationFoldMaker() - Constructor for class weka.gui.beans.CrossValidationFoldMaker
CrossValidationFoldMakerBeanInfo - Class in weka.gui.beans: BeanInfo class for the cross validation fold maker bean
CrossValidationFoldMakerBeanInfo() - Constructor for class weka.gui.beans.CrossValidationFoldMakerBeanInfo
CrossValidationFoldMakerCustomizer - Class in weka.gui.beans: GUI Customizer for the cross validation fold maker bean
CrossValidationFoldMakerCustomizer() - Constructor for class weka.gui.beans.CrossValidationFoldMakerCustomizer
CrossValidationResultProducer - Class in weka.experiment: Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationResultProducer() - Constructor for class weka.experiment.CrossValidationResultProducer
CrossValidationSplitResultProducer - Class in weka.experiment: Carries out one split of a repeated k-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationSplitResultProducer() - Constructor for class weka.experiment.CrossValidationSplitResultProducer
crossValTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
CSV - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions as CSV.
CSV() - Constructor for class weka.classifiers.evaluation.output.prediction.CSV
CSVLoader - Class in weka.core.converters: Reads a source that is in comma separated format (the default).
CSVLoader() - Constructor for class weka.core.converters.CSVLoader: default constructor.
CSVResultListener - Class in weka.experiment: Takes results from a result producer and assembles them into comma separated value form.
CSVResultListener() - Constructor for class weka.experiment.CSVResultListener: Sets temporary file.
CSVSaver - Class in weka.core.converters: Writes to a destination that is in CSV (comma-separated values) format.
CSVSaver() - Constructor for class weka.core.converters.CSVSaver: Constructor.
cTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
cTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
cumulate() - Method in class weka.core.matrix.DoubleVector: Returns a vector that stores the cumulated values of the original vector
cumulateInPlace() - Method in class weka.core.matrix.DoubleVector: Cumulates the original vector in place
cumulativeCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: CumulativeCV returns the accuracy calculated using cumulative cross validation.
CUMULATIVELINKFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for CUMULATIVE-LINK-FUNCTION.
CustomDisplayStringProvider - Interface in weka.core: For classes that do not implement the OptionHandler interface and want to provide a custom display string in the GenericObjectEditor, which is more descriptive than the class name.
customizePopupMenu(JPopupMenu, Object, GenericObjectEditorHistory.HistorySelectionListener) - Method in class weka.gui.GenericObjectEditorHistory: Adds a menu item with the history to the popup menu.
CustomizerCloseRequester - Interface in weka.gui.beans: Customizers who want to be able to close the customizer window themselves can implement this window.
customizerClosing() - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.ClassAssignerCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassifierCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassValuePickerCustomizer
customizerClosing() - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
customizerClosing() - Method in interface weka.gui.beans.CustomizerClosingListener: Customizer classes that want to know when they are being disposed of can implement this method.
customizerClosing() - Method in class weka.gui.beans.DataVisualizerCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.ImageSaverCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
customizerClosing() - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.NoteCustomizer
customizerClosing() - Method in class weka.gui.beans.PredictionAppenderCustomizer
customizerClosing() - Method in class weka.gui.beans.SerializedModelSaverCustomizer
customizerClosing() - Method in class weka.gui.beans.TextSaverCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the TextSaver to its previous state.
CustomizerClosingListener - Interface in weka.gui.beans
CustomPanelSupplier - Interface in weka.gui: An interface for objects that are capable of supplying their own custom GUI components.
customPropsFileTipText() - Method in class weka.core.converters.DatabaseLoader: The tip text for this property.
customPropsFileTipText() - Method in class weka.core.converters.DatabaseSaver: The tip text for this property.
customPropsFileTipText() - Method in class weka.experiment.InstanceQuery: The tip text for this property.
cutoffTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
cutpointsToString(double[], boolean[]) - Static method in class weka.estimators.EstimatorUtils: Returns a string representing the cutpoints
CVParameterSelection - Class in weka.classifiers.meta: Class for performing parameter selection by cross-validation for any classifier.

For more information, see:

R.
CVParameterSelection() - Constructor for class weka.classifiers.meta.CVParameterSelection
CVParametersTipText() - Method in class weka.classifiers.meta.CVParameterSelection: Returns the tip text for this property
CVResultsString() - Method in class weka.attributeSelection.AttributeSelection: returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
CVTypeTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

D

DATA - Static variable in class weka.core.json.JSONInstances: the data section.
DatabaseConnection - Class in weka.core.converters: Connects to a database.
DatabaseConnection() - Constructor for class weka.core.converters.DatabaseConnection: Sets up the database drivers.
DatabaseConnection(File) - Constructor for class weka.core.converters.DatabaseConnection: Reads the properties from the specified file and sets up the database drivers.
DatabaseConnection(Properties) - Constructor for class weka.core.converters.DatabaseConnection: Uses the specified properties to set up the database drivers.
DatabaseConnectionDialog - Class in weka.gui: A dialog to enter URL, username and password for a database connection.
DatabaseConnectionDialog(Frame) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String, boolean) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConverter - Interface in weka.core.converters: Marker interface for a loader/saver that uses a database
DatabaseLoader - Class in weka.core.converters: Reads Instances from a Database.
DatabaseLoader() - Constructor for class weka.core.converters.DatabaseLoader: Constructor
DatabaseResultListener - Class in weka.experiment: Takes results from a result producer and sends them to a database.
DatabaseResultListener() - Constructor for class weka.experiment.DatabaseResultListener: Sets up the database drivers
DatabaseResultProducer - Class in weka.experiment: Examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
DatabaseResultProducer() - Constructor for class weka.experiment.DatabaseResultProducer: Creates the DatabaseResultProducer, letting the parent constructor do it's thing.
DatabaseSaver - Class in weka.core.converters: Writes to a database (tested with MySQL, InstantDB, HSQLDB).
DatabaseSaver() - Constructor for class weka.core.converters.DatabaseSaver: Constructor.
databaseURLTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
DatabaseUtils - Class in weka.experiment: DatabaseUtils provides utility functions for accessing the experiment database.
DatabaseUtils() - Constructor for class weka.experiment.DatabaseUtils: Reads properties and sets up the database drivers.
DatabaseUtils(File) - Constructor for class weka.experiment.DatabaseUtils: Reads the properties from the specified file and sets up the database drivers.
DatabaseUtils(Properties) - Constructor for class weka.experiment.DatabaseUtils: Uses the specified properties to set up the database drivers.
DataDictionary - Class in weka.core.pmml.jaxbbindings: Java class for DataDictionary element declaration.
DataDictionary() - Constructor for class weka.core.pmml.jaxbbindings.DataDictionary
dataDL(double, double, double, double, double) - Static method in class weka.classifiers.rules.RuleStats: The description length of data given the parameters of the data based on the ruleset.
DataField - Class in weka.core.pmml.jaxbbindings: Java class for DataField element declaration.
DataField() - Constructor for class weka.core.pmml.jaxbbindings.DataField
DataField(String, OPTYPE) - Constructor for class weka.core.pmml.jaxbbindings.DataField
DataFormatListener - Interface in weka.gui.beans: Listener interface that customizer classes that are interested in data format changes can implement.
DataGenerator - Class in weka.datagenerators: Abstract superclass for data generators that generate data for classifiers and clusterers.
DataGenerator() - Constructor for class weka.datagenerators.DataGenerator: initializes with default settings.
DataGenerator - Interface in weka.gui.boundaryvisualizer: Interface to something that can generate new instances based on a set of input instances
DataGeneratorPanel - Class in weka.gui.explorer: A panel for generating artificial data via DataGenerators.
DataGeneratorPanel() - Constructor for class weka.gui.explorer.DataGeneratorPanel: creates the panel
dataset() - Method in class weka.core.AbstractInstance: Returns the dataset this instance has access to.
dataset() - Method in interface weka.core.Instance: Returns the dataset this instance has access to.
DATASET_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the key field containing the dataset name
DATASET_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer: The name of the key field containing the dataset name.
DATASET_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer: The name of the key field containing the dataset name
DataSetEvent - Class in weka.gui.beans: Event encapsulating a data set
DataSetEvent(Object, Instances) - Constructor for class weka.gui.beans.DataSetEvent
DatasetListPanel - Class in weka.gui.experiment: This panel controls setting a list of datasets for an experiment to iterate over.
DatasetListPanel(Experiment) - Constructor for class weka.gui.experiment.DatasetListPanel: Creates the dataset list panel with the given experiment.
DatasetListPanel() - Constructor for class weka.gui.experiment.DatasetListPanel: Create the dataset list panel initially disabled.
DataSink - Interface in weka.gui.beans: Indicator interface to something that can store instances to some destination
DataSource - Interface in weka.gui.beans: Interface to something that is capable of being a source for data - either batch or incremental data
DataSourceListener - Interface in weka.gui.beans: Interface to something that can accept DataSetEvents
DATATYPE - Enum in weka.core.pmml.jaxbbindings: Java class for DATATYPE.
DATATYPE_LAYOUT - Static variable in class weka.gui.beans.xml.XMLBeans: the data that is about to be read/written contains a complete layout
DATATYPE_USERCOMPONENTS - Static variable in class weka.gui.beans.xml.XMLBeans: the data that is about to be read/written contains user-components, i.e., Metabeans
DataVisualizer - Class in weka.gui.beans: Bean that encapsulates weka.gui.visualize.VisualizePanel
DataVisualizer() - Constructor for class weka.gui.beans.DataVisualizer
DataVisualizerBeanInfo - Class in weka.gui.beans: Bean info class for the data visualizer
DataVisualizerBeanInfo() - Constructor for class weka.gui.beans.DataVisualizerBeanInfo
DataVisualizerCustomizer - Class in weka.gui.beans: GUI customizer for data visualizer.
DataVisualizerCustomizer() - Constructor for class weka.gui.beans.DataVisualizerCustomizer: Constructor
DATE - Static variable in class weka.core.Attribute: Constant set for attributes with date values.
DATE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for DATE used for reading experiment results.
dateAttributesTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
DATEFORMAT - Static variable in class weka.core.json.JSONInstances: the dateformat attribute.
dateFormatTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
dateReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
DbConnectionDialog(String, String) - Method in class weka.gui.DatabaseConnectionDialog: Display the database connection dialog
DbConnectionDialog(String, String, boolean) - Method in class weka.gui.DatabaseConnectionDialog: Display the database connection dialog
DbUtils - Class in weka.gui.sql: A little bit extended DatabaseUtils class.
DbUtils() - Constructor for class weka.gui.sql.DbUtils: initializes the object.
dchisq(double) - Static method in class weka.core.matrix.Maths: Returns the density of the Chi-squared distribution.
dchisq(double, double) - Static method in class weka.core.matrix.Maths: Returns the density of the noncentral Chi-squared distribution.
dchisq(double, DoubleVector) - Static method in class weka.core.matrix.Maths: Returns the density of the noncentral Chi-squared distribution.
dchisqLog(double) - Static method in class weka.core.matrix.Maths: Returns the log-density of the noncentral Chi-square distribution.
dchisqLog(double, double) - Static method in class weka.core.matrix.Maths: Returns the log-density value of a noncentral Chi-square distribution.
dchisqLog(double, DoubleVector) - Static method in class weka.core.matrix.Maths: Returns the log-density of a set of noncentral Chi-squared distributions.
DDConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a discrete domain.
DDConditionalEstimator(int, int, boolean) - Constructor for class weka.estimators.DDConditionalEstimator: Constructor
Debug - Class in weka.core: A helper class for debug output, logging, clocking, etc.
Debug() - Constructor for class weka.core.Debug: default constructor, prints only to stdout
Debug(String) - Constructor for class weka.core.Debug: logs the output to the specified file (and stdout).
Debug(String, int, int) - Constructor for class weka.core.Debug: logs the output
DEBUG - Static variable in class weka.gui.LogWindow: whether we're debugging - enables output on stdout
Debug.Clock - Class in weka.core: A little helper class for clocking and outputting times.
Debug.Clock() - Constructor for class weka.core.Debug.Clock: automatically starts the clock with FORMAT_SECONDS format and CPU time if available
Debug.Clock(int) - Constructor for class weka.core.Debug.Clock: automatically starts the clock with the given output format and CPU time if available
Debug.Clock(boolean) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately with the FORMAT_SECONDS output format and CPU time if available
Debug.Clock(boolean, int) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately, using CPU time if available
Debug.DBO - Class in weka.core: contains debug methods
Debug.DBO() - Constructor for class weka.core.Debug.DBO
Debug.Log - Class in weka.core: A helper class for logging stuff.
Debug.Log() - Constructor for class weka.core.Debug.Log: default constructor, uses only stdout
Debug.Log(String) - Constructor for class weka.core.Debug.Log: creates a logger that logs into the specified file, if null then only stdout is used.
Debug.Log(String, int, int) - Constructor for class weka.core.Debug.Log: creates a logger that logs into the specified file, if null then only stdout is used.
Debug.Random - Class in weka.core: This extended Random class enables one to print the generated random numbers etc., before they are returned.
Debug.Random() - Constructor for class weka.core.Debug.Random: Creates a new random number generator.
Debug.Random(long) - Constructor for class weka.core.Debug.Random: Creates a new random number generator using a single long seed.
Debug.Random(boolean) - Constructor for class weka.core.Debug.Random: Creates a new random number generator.
Debug.Random(long, boolean) - Constructor for class weka.core.Debug.Random: Creates a new random number generator using a single long seed.
Debug.SimpleLog - Class in weka.core: A little, simple helper class for logging stuff.
Debug.SimpleLog() - Constructor for class weka.core.Debug.SimpleLog: default constructor, uses only stdout
Debug.SimpleLog(String) - Constructor for class weka.core.Debug.SimpleLog: Creates a logger that writes into the specified file.
Debug.SimpleLog(String, boolean) - Constructor for class weka.core.Debug.SimpleLog: Creates a logger that writes into the specified file.
Debug.Timestamp - Class in weka.core: A class that can be used for timestamps in files, The toString() method simply returns the associated Date object in a timestamp format.
Debug.Timestamp() - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the current date and time and the default format.
Debug.Timestamp(String) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the current date and time and the specified format.
Debug.Timestamp(Date) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the given date and the default format.
Debug.Timestamp(Date, String) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the given date and format.
debuggingOutputTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
debugTipText() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.AbstractClusterer: Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
debugTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
debugTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
debugTipText() - Method in class weka.estimators.Estimator: Returns the tip text for this property
debugTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
debugTipText() - Method in class weka.filters.SimpleFilter: Returns the tip text for this property
debugTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the tip text for this property
decayTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
decimalsTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
Decision - Class in weka.core.pmml.jaxbbindings: Java class for Decision element declaration.
Decision() - Constructor for class weka.core.pmml.jaxbbindings.Decision
Decisions - Class in weka.core.pmml.jaxbbindings: Java class for Decisions element declaration.
Decisions() - Constructor for class weka.core.pmml.jaxbbindings.Decisions
DecisionStump - Class in weka.classifiers.trees: Class for building and using a decision stump.
DecisionStump() - Constructor for class weka.classifiers.trees.DecisionStump
DecisionTable - Class in weka.classifiers.rules: Class for building and using a simple decision table majority classifier.

For more information see:

Ron Kohavi: The Power of Decision Tables.
DecisionTable() - Constructor for class weka.classifiers.rules.DecisionTable: Constructor for a DecisionTable
DecisionTableHashKey - Class in weka.classifiers.rules: Class providing hash table keys for DecisionTable
DecisionTableHashKey(Instance, int, boolean) - Constructor for class weka.classifiers.rules.DecisionTableHashKey: Constructor for a hashKey
DecisionTableHashKey(double[]) - Constructor for class weka.classifiers.rules.DecisionTableHashKey: Constructor for a hashKey
DecisionTree - Class in weka.core.pmml.jaxbbindings: Java class for DecisionTree element declaration.
DecisionTree() - Constructor for class weka.core.pmml.jaxbbindings.DecisionTree
decompose() - Method in class weka.classifiers.BVDecompose: Carry out the bias-variance decomposition
decompose() - Method in class weka.classifiers.BVDecomposeSegCVSub: Carry out the bias-variance decomposition using the sub-sampled cross-validation method.
decreaseFontSize() - Method in class weka.gui.beans.Note: Decrease the font size by one
decreaseFrequency(int) - Method in class weka.associations.Item: Decrease the frequency of this item.
decreaseFrequency() - Method in class weka.associations.Item: Decrement the frequency of this item.
DEFAULT_COLORS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel: default colours for classes
DEFAULT_COMMENT - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for comments.
DEFAULT_EXPRESSION - Static variable in class weka.filters.unsupervised.attribute.RemoveByName: the default expression.
DEFAULT_FONT_FAMILY - Static variable in class weka.gui.scripting.SyntaxDocument: the font family.
DEFAULT_FONT_SIZE - Static variable in class weka.gui.scripting.SyntaxDocument: the font size.
DEFAULT_FORMAT - Static variable in class weka.core.Debug.Timestamp: the default format
DEFAULT_FORMAT - Static variable in class weka.gui.SimpleDateFormatEditor: the default format
DEFAULT_HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for height
DEFAULT_KEYWORD - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for keywords.
DEFAULT_LEFT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for left
DEFAULT_NORMAL - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for normal code.
DEFAULT_PACKAGE - Static variable in class weka.core.ClassCache: the key for the default package.
DEFAULT_SEPARATORS - Static variable in class weka.core.TestInstances: the default word separators used in strings
DEFAULT_SHAPE_SIZE - Static variable in class weka.gui.visualize.Plot2D
DEFAULT_STRING - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for strings.
DEFAULT_SUFFIX - Static variable in class weka.experiment.ExplicitTestsetResultProducer: the default suffix.
DEFAULT_T1 - Static variable in class weka.clusterers.Canopy
DEFAULT_T2 - Static variable in class weka.clusterers.Canopy
DEFAULT_TOP - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for top
DEFAULT_WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for width
DEFAULT_WORDS - Static variable in class weka.core.TestInstances: the default list of words used in strings
DefaultAssociationRule - Class in weka.associations: Class for storing and manipulating an association rule.
DefaultAssociationRule(Collection<Item>, Collection<Item>, DefaultAssociationRule.METRIC_TYPE, int, int, int, int) - Constructor for class weka.associations.DefaultAssociationRule: Construct a new default association rule.
DefaultAssociationRule.METRIC_TYPE - Enum in weka.associations: Enum for holding different metric types
defaultOutput() - Method in class weka.datagenerators.DataGenerator: Gets writer, which is used for outputting to stdout.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.LED24: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RDG1: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.Expression: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.DataGenerator: Initializes the format for the dataset produced.
DefineFunction - Class in weka.core.pmml: Class encapsulating DefineFunction (used in TransformationDictionary).
DefineFunction(Element, TransformationDictionary) - Constructor for class weka.core.pmml.DefineFunction
DefineFunction - Class in weka.core.pmml.jaxbbindings: Java class for DefineFunction element declaration.
DefineFunction() - Constructor for class weka.core.pmml.jaxbbindings.DefineFunction
del(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Deletes given instance from given bag.
delete(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Deletes an element from the set.
delete() - Method in class weka.core.Instances: Removes all instances from the set.
delete(int) - Method in class weka.core.Instances: Removes an instance at the given position from the set.
deleteArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete arc between two nodes.
deleteArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete arc between two nodes.
deleteAttribute() - Method in class weka.gui.arffviewer.ArffPanel: deletes the currently selected attribute
deleteAttribute(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: deletes the current selected Attribute or several chosen ones
deleteAttributeAt(int) - Method in class weka.core.AbstractInstance: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in interface weka.core.Instance: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.core.Instances: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the attribute at the given col index
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attribute at the given col index.
deleteAttributeAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attribute at the given col index
deleteAttributes() - Method in class weka.gui.arffviewer.ArffPanel: deletes the chosen attributes
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the attributes at the given indices
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attributes at the given indices
deleteAttributeType(int) - Method in class weka.core.Instances: Deletes all attributes of the given type in the dataset.
deleteEmptyBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
deleteInstance() - Method in class weka.gui.arffviewer.ArffPanel: deletes the currently selected instance
deleteInstance(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: deletes the current selected Instance or several chosen ones
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the instance at the given index
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instance at the given index
deleteInstances() - Method in class weka.gui.arffviewer.ArffPanel: deletes all the currently selected instances
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the instances at the given positions
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instances at the given positions
deleteItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.ItemSet: Deletes all item sets that don't have minimum support.
deleteItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.LabeledItemSet: Deletes all item sets that don't have minimum support and have more than maximum support
deleteLastParent(Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Delete last added parent from parent set and update internals (specifically the cardinality of the parent set)
deleteNode(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteNode(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: delete node from parent set
deleteSelection(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteStringAttributes() - Method in class weka.core.Instances: Deletes all string attributes in the dataset.
deleteWithMissing(int) - Method in class weka.core.Instances: Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(Attribute) - Method in class weka.core.Instances: Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissingClass() - Method in class weka.core.Instances: Removes all instances with a missing class value from the dataset.
Delimiter - Class in weka.core.pmml.jaxbbindings: Java class for Delimiter element declaration.
Delimiter() - Constructor for class weka.core.pmml.jaxbbindings.Delimiter
DELIMITER2 - Enum in weka.core.pmml.jaxbbindings: Java class for DELIMITER.
delimitersTipText() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Returns the tip text for this property
delNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node value from a node.
delRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Deletes all instances in given range from given bag.
deltaTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
deltaTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
deltaTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
deltaTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
DenseInstance - Class in weka.core: Class for handling an instance.
DenseInstance(Instance) - Constructor for class weka.core.DenseInstance: Constructor that copies the attribute values and the weight from the given instance.
DenseInstance(double, double[]) - Constructor for class weka.core.DenseInstance: Constructor that inititalizes instance variable with given values.
DenseInstance(int) - Constructor for class weka.core.DenseInstance: Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
DensityBasedClusterer - Interface in weka.clusterers: Interface for clusterers that can estimate the density for a given instance.
DensityBasedClustererSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a density based clusterer.
DensityBasedClustererSplitEvaluator() - Constructor for class weka.experiment.DensityBasedClustererSplitEvaluator
densityBasedClustererTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns a description of this option suitable for display as a tip text in the gui.
dependencies() - Method in class weka.core.Capabilities: Returns an Iterator over the stored dependencies
depth() - Method in class weka.gui.HierarchyPropertyParser: Get the depth of the tree, i.e.
DerivedField - Class in weka.core.pmml.jaxbbindings: Java class for DerivedField element declaration.
DerivedField() - Constructor for class weka.core.pmml.jaxbbindings.DerivedField
DerivedField(String, DATATYPE, OPTYPE) - Constructor for class weka.core.pmml.jaxbbindings.DerivedField
DerivedFieldMetaInfo - Class in weka.core.pmml
DerivedFieldMetaInfo(Element, ArrayList<Attribute>, TransformationDictionary) - Constructor for class weka.core.pmml.DerivedFieldMetaInfo
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
description() - Method in class weka.core.Option: Returns the option's description.
deserialize(InputStream) - Static method in class weka.core.scripting.Jython: deserializes the Python Object from the stream
deSerialize(String) - Static method in class weka.core.xml.XStream: Deserializes an object from the supplied XML string
desiredWeightOfInstancesPerIntervalTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
dest - Variable in class weka.gui.graphvisualizer.GraphEdge: The index of target node in Nodes vector
destLbl - Variable in class weka.gui.graphvisualizer.GraphEdge: Label of target node
det() - Method in class weka.core.matrix.LUDecomposition: Determinant
det() - Method in class weka.core.matrix.Matrix: Matrix determinant
detectionPerAttributeTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
determineBounds() - Method in class weka.gui.visualize.Plot2D: Determine the min and max values for axis and colouring attributes
determineClasses() - Static method in class weka.gui.GenericObjectEditor
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.AveragingResultProducer: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.CSVResultListener: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.DatabaseResultListener: Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in interface weka.experiment.ResultListener: Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
determineValues(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: determines the values to retain, it is always at least 1 and up to the maximum number of distinct values
DIAMOND_SHAPE - Static variable in class weka.gui.visualize.Plot2D
differencesProbability - Variable in class weka.experiment.PairedStats: The probability of obtaining the observed differences
differencesSignificance - Variable in class weka.experiment.PairedStats: A significance indicator: 0 if the differences are not significant > 0 if x significantly greater than y < 0 if x significantly less than y
differencesStats - Variable in class weka.experiment.PairedStats: The stats associated with the paired differences
DIRECTED - Static variable in interface weka.gui.graphvisualizer.GraphConstants: Types of Edges
directionTipText() - Method in class weka.attributeSelection.BestFirst: Returns the tip text for this property
disable(Capabilities.Capability) - Method in class weka.core.Capabilities: disables the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: disables the given capability.
disableAll() - Method in class weka.core.Capabilities: disables all attribute and class types (including dependencies)
disableAllAttributeDependencies() - Method in class weka.core.Capabilities: disables all attribute type dependencies
disableAllAttributes() - Method in class weka.core.Capabilities: disables all attribute types
disableAllClassDependencies() - Method in class weka.core.Capabilities: disables all class type dependencies
disableAllClasses() - Method in class weka.core.Capabilities: disables all class types
disableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: disables the dependency of the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: disables the given "not to have" capability.
disconnect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection: Disconnects two units.
DISCONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent: it was a disconnect
disconnectFromDatabase() - Method in class weka.experiment.DatabaseUtils: Closes the connection to the database.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event named
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Appender: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Associator: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Classifier: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name This method should be implemented synchronized.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.CrossValidationFoldMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.DataVisualizer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Filter: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.FlowByExpression
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ImageSaver
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ImageViewer
disconnectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Join: Handles cleanup when an upstream step disconnects
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Loader: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ModelPerformanceChart: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Sorter: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.StripChart: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SubstringLabeler: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SubstringReplacer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TextSaver
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TrainTestSplitMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
DiscreteEstimator - Class in weka.estimators: Simple symbolic probability estimator based on symbol counts.
DiscreteEstimator(int, boolean) - Constructor for class weka.estimators.DiscreteEstimator: Constructor
DiscreteEstimator(int, double) - Constructor for class weka.estimators.DiscreteEstimator: Constructor
DiscreteEstimatorBayes - Class in weka.classifiers.bayes.net.estimate: Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorBayes(int, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Constructor
DiscreteEstimatorFullBayes - Class in weka.classifiers.bayes.net.estimate: Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorFullBayes(int, double, double, DiscreteEstimatorBayes, DiscreteEstimatorBayes, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes: Constructor
Discretize - Class in weka.core.pmml: Class encapsulating a Discretize Expression.
Discretize(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Discretize: Constructs a Discretize Expression
Discretize - Class in weka.core.pmml.jaxbbindings: Java class for Discretize element declaration.
Discretize() - Constructor for class weka.core.pmml.jaxbbindings.Discretize
Discretize - Class in weka.filters.supervised.attribute: An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.supervised.attribute.Discretize: Constructor - initialises the filter
Discretize - Class in weka.filters.unsupervised.attribute: An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.unsupervised.attribute.Discretize: Constructor - initialises the filter
Discretize(String) - Constructor for class weka.filters.unsupervised.attribute.Discretize: Another constructor, sets the attribute indices immediately
DiscretizeBin - Class in weka.core.pmml.jaxbbindings: Java class for DiscretizeBin element declaration.
DiscretizeBin() - Constructor for class weka.core.pmml.jaxbbindings.DiscretizeBin
DiscrStats - Class in weka.core.pmml.jaxbbindings: Java class for DiscrStats element declaration.
DiscrStats() - Constructor for class weka.core.pmml.jaxbbindings.DiscrStats
displayModelInOldFormatTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
displayModelInOldFormatTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
displayResultset(int) - Method in class weka.experiment.PairedTTester: Checks whether the resultset with the given index shall be displayed.
displayResultset(int) - Method in interface weka.experiment.Tester: Checks whether the resultset with the given index shall be displayed.
displayRulesTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
displayStdDevsTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
dispose() - Method in class weka.gui.GUIChooser.ChildFrameSDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameMDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameSDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
disposeSingleton() - Static method in class weka.gui.beans.KnowledgeFlowApp
disposeSplash() - Static method in class weka.gui.SplashWindow: Closes the splash window.
distance(Instance, Instance) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance) - Method in class weka.core.EuclideanDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.EuclideanDistance: Calculates the distance (or similarity) between two instances.
distance(Instance, Instance) - Method in class weka.core.MinkowskiDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.MinkowskiDistance: Calculates the distance (or similarity) between two instances.
distance(Instance, Instance) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
DistanceFunction - Interface in weka.core: Interface for any class that can compute and return distances between two instances.
distanceFunctionTipText() - Method in class weka.clusterers.HierarchicalClusterer
distanceFunctionTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
distanceFunctionTipText() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the tip text for this property.
distanceIsBranchLengthTipText() - Method in class weka.clusterers.HierarchicalClusterer
distanceWeightingTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
distinctCount - Variable in class weka.core.AttributeStats: The number of distinct values
distMultTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
distributedExperimentSelected() - Method in class weka.gui.experiment.DistributeExperimentPanel: Returns true if the distribute experiment checkbox is selected
DistributeExperimentPanel - Class in weka.gui.experiment: This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
DistributeExperimentPanel() - Constructor for class weka.gui.experiment.DistributeExperimentPanel: Constructor
DistributeExperimentPanel(Experiment) - Constructor for class weka.gui.experiment.DistributeExperimentPanel: Creates the panel with the supplied initial experiment.
distribution() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the predicted probabilities
distribution() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns the distribution of class values induced by the model.
Distribution - Class in weka.classifiers.trees.j48: Class for handling a distribution of class values.
Distribution(int, int) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates and initializes a new distribution.
Distribution(double[][]) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates and initializes a new distribution using the given array.
Distribution(Instances) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates a distribution with only one bag according to instances in source.
Distribution(Instances, ClassifierSplitModel) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates a distribution according to given instances and split model.
Distribution(Distribution) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates distribution with only one bag by merging all bags of given distribution.
Distribution(Distribution, int) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates distribution with two bags by merging all bags apart of the indicated one.
distributionForInstance(Instance) - Method in class weka.classifiers.AbstractClassifier: Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayes: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in interface weka.classifiers.Classifier: Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.Logistic: Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.MultilayerPerceptron: Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SGD: Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SGDText
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SimpleLogistic: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SMO: Estimates class probabilities for given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.VotedPerceptron: Outputs the distribution for the given output.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.IBk: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.KStar: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWL: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AdaBoostM1: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Classifies a given instance after attribute selection
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Bagging: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CVParameterSelection: Predicts the class distribution for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifier: Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.LogitBoost: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiScheme: Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomCommittee: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomSubSpace: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Stacking: Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Vote: Classifies a given instance using the selected combination rule.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
distributionForInstance(Instance) - Method in class weka.classifiers.misc.SerializedClassifier: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.GeneralRegression: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.NeuralNetwork: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.Regression: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.RuleSetModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.TreeModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.DecisionTable: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.JRip: Classify the test instance with the rule learner and provide the class distributions
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.PART: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList: Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ZeroR: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.DecisionStump: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.HoeffdingTree: Returns class probabilities for an instance.
distributionForInstance(Instance, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.J48: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LMT: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the class probabilities for an instance given by the logistic model tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomForest: Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomTree: Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.REPTree: Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractClusterer: Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.clusterers.Canopy
distributionForInstance(Instance) - Method in interface weka.clusterers.Clusterer: Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer: Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.clusterers.FilteredClusterer: Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
distributionsByOriginalIndex(double[]) - Method in class weka.filters.supervised.attribute.ClassOrder: Convert the given class distribution back to the distributions with the original internal class index
distributionsForInstances(Instances) - Method in interface weka.core.BatchPredictor: Batch scoring method
distributionSpreadTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
distributionTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
divergence(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: calculates the divergence between the probability distribution represented by this network and that of another, that is, \sum_{x\in X} P(x)log P(x)/Q(x) where X is the set of values the nodes in the network can take, P(x) the probability of this network for configuration x Q(x) the probability of the other network for configuration x
divide(Instances, boolean) - Static method in class weka.associations.LabeledItemSet: Splits the class attribute away.
dividedBy(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Divided by another DoubleVector element by element
dividedByEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Divided by another DoubleVector element by element in place
DIVISION - Static variable in interface weka.core.mathematicalexpression.sym
DIVISION - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
DKConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DKConditionalEstimator(int, double) - Constructor for class weka.estimators.DKConditionalEstimator: Constructor
dl(int) - Method in class weka.core.Debug.DBO: Return true if the debug level is set same method as outpuTypeSet but better name
DNConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DNConditionalEstimator(int, double) - Constructor for class weka.estimators.DNConditionalEstimator: Constructor
dnorm(double) - Static method in class weka.core.matrix.Maths: Returns the density of the standard normal.
dnorm(double, double, double) - Static method in class weka.core.matrix.Maths: Returns the density value of a standard normal.
dnorm(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths: Returns the density values of a set of normal distributions with different means.
dnormLog(double) - Static method in class weka.core.matrix.Maths: Returns the log-density of the standard normal.
dnormLog(double, double, double) - Static method in class weka.core.matrix.Maths: Returns the log-density value of a standard normal.
dnormLog(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths: Returns the log-density values of a set of normal distributions with different means.
do_action(int, lr_parser, Stack, int) - Method in class weka.core.json.Parser: Invoke a user supplied parse action.
do_action(int, lr_parser, Stack, int) - Method in class weka.core.mathematicalexpression.Parser: Invoke a user supplied parse action.
do_action(int, lr_parser, Stack, int) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser: Invoke a user supplied parse action.
doCommandlineCompletion(KeyEvent) - Method in class weka.gui.SimpleCLIPanel: performs commandline completion on packages and classnames.
DOCTYPE - Static variable in class weka.core.xml.XMLInstances: the DTD
DOCTYPE - Static variable in class weka.core.xml.XMLOptions: the DTD for the XML file.
DOCTYPE - Static variable in class weka.core.xml.XMLSerialization: the DOCTYPE for the serialization
DocumentPrinting - Class in weka.gui: DocumentPrinting is a class that lets you print documents on the fly for free ;) Printing in JDK 1.2 - 1.5 is hard.
DocumentPrinting() - Constructor for class weka.gui.DocumentPrinting: Initializes the printing.
DocumentTermMatrix - Class in weka.core.pmml.jaxbbindings: Java class for DocumentTermMatrix element declaration.
DocumentTermMatrix() - Constructor for class weka.core.pmml.jaxbbindings.DocumentTermMatrix
doHistory(KeyEvent) - Method in class weka.gui.SimpleCLIPanel: Changes the currently displayed command line when certain keys are pressed.
doLayout() - Method in class weka.gui.beans.EnvironmentField.WideComboBox
doMetaConnection(BeanInstance, BeanInstance, EventSetDescriptor, JComponent, int) - Static method in class weka.gui.beans.BeanConnection
done() - Method in interface weka.classifiers.IterativeClassifier: Signal end of iterating, useful for any house-keeping/cleanup
done() - Method in class weka.classifiers.meta.LogitBoost: Clean up after boosting.
done() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Signal that a scoring run has been completed.
doNotCheckCapabilitiesTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.clusterers.AbstractClusterer: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.filters.SimpleFilter: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
doNotOperateOnPerClassBasisTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
doNotPrintModelsTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
dontCalculateOutOfBagErrorTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
dontDisplayMetrics(List<String>) - Method in class weka.classifiers.Evaluation: Remove the supplied list of metrics from the list of those to display.
dontDisplayMetrics(List<String>) - Method in class weka.classifiers.evaluation.Evaluation: Remove the supplied list of metrics from the list of those to display.
dontFilterAfterFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property.
dontNormalizeTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
dontNormalizeTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
dontReplaceMissingTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
dontShowOKCancelButtons() - Method in interface weka.gui.beans.GOECustomizer: Tells the customizer not to display its own OK and CANCEL buttons
dontShowOKCancelButtons() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Tell this customizer not to show its own OK and Cancel buttons.
doRun(int) - Method in class weka.experiment.AveragingResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.DatabaseResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.LearningRateResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.RandomSplitResultProducer: Gets the results for a specified run number.
doRun(int) - Method in interface weka.experiment.ResultProducer: Gets the results for a specified run number.
doRunKeys(int) - Method in class weka.experiment.AveragingResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.DatabaseResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.LearningRateResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.RandomSplitResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in interface weka.experiment.ResultProducer: Gets the keys for a specified run number.
doTests() - Method in class weka.associations.CheckAssociator: Begin the tests, reporting results to System.out
doTests() - Method in class weka.attributeSelection.CheckAttributeSelection: Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.CheckClassifier: Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Begin the tests, reporting results to System.out
doTests() - Method in class weka.clusterers.CheckClusterer: Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.Check: Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.CheckGOE: Runs some diagnostic tests on the object.
doTests() - Method in class weka.core.CheckOptionHandler: Runs some diagnostic tests on an optionhandler object.
doTests() - Method in class weka.core.CheckScheme: Begin the tests, reporting results to System.out
doTests() - Method in class weka.estimators.CheckEstimator: Begin the tests, reporting results to System.out
dotMultiply(AlgVector) - Method in class weka.core.AlgVector: Returns the inner (or dot) product of two vectors
DotParser - Class in weka.gui.graphvisualizer: This class parses input in DOT format, and builds the datastructures that are passed to it.
DotParser(Reader, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.DotParser: Dot parser Constructor
dotProduct(VectorInstance) - Method in class weka.core.pmml.VectorInstance: Computes the dot product between this vector instance and the argument
dotProduct(double[]) - Method in class weka.core.pmml.VectorInstance: Computes the dot product between this vector instance and the supplied array of values
DOUBLE - Static variable in interface weka.core.json.sym
DOUBLE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for DOUBLE used for reading experiment results.
DOUBLE - Static variable in interface weka.gui.graphvisualizer.GraphConstants: Types of Edges
doubleToString(double, int) - Static method in class weka.core.Utils: Rounds a double and converts it into String.
doubleToString(double, int, int) - Static method in class weka.core.Utils: Rounds a double and converts it into a formatted decimal-justified String.
DoubleVector - Class in weka.core.matrix: A vector specialized on doubles.
DoubleVector() - Constructor for class weka.core.matrix.DoubleVector: Constructs a null vector.
DoubleVector(int) - Constructor for class weka.core.matrix.DoubleVector: Constructs an n-vector of zeros.
DoubleVector(int, double) - Constructor for class weka.core.matrix.DoubleVector: Constructs a constant n-vector.
DoubleVector(double[]) - Constructor for class weka.core.matrix.DoubleVector: Constructs a vector directly from a double array
dp(String) - Method in class weka.core.Debug.DBO: prints out text if verbose is on.
dp(int, String) - Method in class weka.core.Debug.DBO: prints out text but only if debug level is set.
dpln(String) - Method in class weka.core.Debug.DBO: prints out text + endofline if verbose is on.
dpln(int, String) - Method in class weka.core.Debug.DBO: prints out text + endofline but only if parameter debug type is set.
draw(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
draw3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an outlined rectangle with 3D effect in current pen color.
Drawable - Interface in weka.core: Interface to something that can be drawn as a graph.
drawArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawBytes(byte[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: simply calls drawString(String,int,int)
drawChars(char[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: simply calls drawString(String,int,int)
drawGlyphVector(GlyphVector, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawHighlight(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the node highlighted.
drawImage(Image, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,Color,ImageObserver)
drawImage(Image, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(Image, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: PS see http://astronomy.swin.edu.au/~pbourke/geomformats/postscript/ Java http ://show.docjava.com:8086/book/cgij/doc/ip/graphics/SimpleImageFrame.java .html
drawImage(Image, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,Color,ImageObserver) with the color WHITE as background
drawImage(Image, int, int, int, int, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawImage(Image, int, int, int, int, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,int,int,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(BufferedImage, BufferedImageOp, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
drawImage(Image, AffineTransform, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
drawInputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the nodes input connections.
drawLine(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a line in current pen color.
drawNode(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the node.
drawOutputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the nodes output connections.
drawOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an Oval outline in current pen color.
drawPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawPolyline(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an outlined rectangle in current pen color.
drawRenderableImage(RenderableImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRenderedImage(RenderedImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawString(AttributedCharacterIterator, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawString(String, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw text in current pen color.
drawString(AttributedCharacterIterator, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawString(String, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
DTD - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the DTD.
DTD_ANY - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the ANY placeholder.
DTD_ANY - Static variable in class weka.core.xml.XMLDocument: the ANY placeholder.
DTD_AT_LEAST_ONE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the at least one marker.
DTD_AT_LEAST_ONE - Static variable in class weka.core.xml.XMLDocument: the at least one marker.
DTD_ATTLIST - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the AttList definition.
DTD_ATTLIST - Static variable in class weka.core.xml.XMLDocument: the AttList definition.
DTD_CDATA - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the CDATA placeholder.
DTD_CDATA - Static variable in class weka.core.xml.XMLDocument: the CDATA placeholder.
DTD_DOCTYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the DocType definition.
DTD_DOCTYPE - Static variable in class weka.core.xml.XMLDocument: the DocType definition.
DTD_ELEMENT - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the Element definition.
DTD_ELEMENT - Static variable in class weka.core.xml.XMLDocument: the Element definition.
DTD_IMPLIED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #IMPLIED placeholder.
DTD_IMPLIED - Static variable in class weka.core.xml.XMLDocument: the #IMPLIED placeholder.
DTD_OPTIONAL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the optional marker.
DTD_OPTIONAL - Static variable in class weka.core.xml.XMLDocument: the optional marker.
DTD_PCDATA - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #PCDATA placeholder.
DTD_PCDATA - Static variable in class weka.core.xml.XMLDocument: the #PCDATA placeholder.
DTD_REQUIRED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #REQUIRED placeholder.
DTD_REQUIRED - Static variable in class weka.core.xml.XMLDocument: the #REQUIRED placeholder.
DTD_SEPARATOR - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the option separator.
DTD_SEPARATOR - Static variable in class weka.core.xml.XMLDocument: the option separator.
DTD_ZERO_OR_MORE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the zero or more marker.
DTD_ZERO_OR_MORE - Static variable in class weka.core.xml.XMLDocument: the zero or more marker.
DUMMY_STRING_VAL - Static variable in class weka.core.Attribute: Dummy first value for String attributes (useful for sparse instances)
dumpDistribution() - Method in class weka.classifiers.trees.j48.Distribution: Prints distribution.
dumpLabel(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints label for subset index of instances (eg class).
dumpModel(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints the split model.

E

EAST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
Edge - Class in weka.gui.treevisualizer: This class is used in conjunction with the Node class to form a tree structure.
Edge(String, String, String) - Constructor for class weka.gui.treevisualizer.Edge: This constructs an Edge with the specified label and parent , child serial tags.
edges - Variable in class weka.gui.graphvisualizer.GraphNode: The indices of nodes to which there are edges from this node, plus the type of edge
edit() - Method in class weka.gui.explorer.PreprocessPanel: edits the current instances object in the viewer
EditableBayesNet - Class in weka.classifiers.bayes.net: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
EditableBayesNet() - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: standard constructor *
EditableBayesNet(Instances) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor, creates empty network with nodes based on the attributes in a data set
EditableBayesNet(BIFReader) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
EditableBayesNet(boolean) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor that potentially initializes instances as well
editableProperties() - Method in class weka.gui.PropertySheetPanel: Gets the number of editable properties for the current target.
eig() - Method in class weka.core.matrix.Matrix: Eigenvalue Decomposition
EigenvalueDecomposition - Class in weka.core.matrix: Eigenvalues and eigenvectors of a real matrix.
eigenvalueDecomposition(double[][], double[]) - Method in class weka.core.Matrix: Deprecated. Performs Eigenvalue Decomposition using Householder QR Factorization Matrix must be symmetrical.
EigenvalueDecomposition(Matrix) - Constructor for class weka.core.matrix.EigenvalueDecomposition: Check for symmetry, then construct the eigenvalue decomposition
element(int) - Method in class weka.core.neighboursearch.covertrees.Stack: Returns the ith element in the stack.
elementAt(int) - Method in class weka.core.FastVector: Deprecated. Returns the element at the given position.
elementAt(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the component at the specified index.
elements() - Method in class weka.core.FastVector: Deprecated. Returns an enumeration of this vector.
elements(int) - Method in class weka.core.FastVector: Deprecated. Returns an enumeration of this vector, skipping the element with the given index.
elements - Variable in class weka.core.neighboursearch.covertrees.Stack: The elements inside the stack.
elements() - Method in class weka.core.Stopwords: Returns a sorted enumeration over all stored stopwords
eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
EM - Class in weka.clusterers: Simple EM (expectation maximisation) class.

EM assigns a probability distribution to each instance which indicates the probability of it belonging to each of the clusters.
EM() - Constructor for class weka.clusterers.EM: Constructor.
empty() - Method in class weka.core.Queue: Checks if queue is empty.
empty() - Method in class weka.gui.scripting.Script: Empties the document.
enable(Capabilities.Capability) - Method in class weka.core.Capabilities: enables the given capability.
enable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: enables the given capability.
enableAll() - Method in class weka.core.Capabilities: enables all attribute and class types (including dependencies)
enableAllAttributeDependencies() - Method in class weka.core.Capabilities: enables all attribute type dependencies
enableAllAttributes() - Method in class weka.core.Capabilities: enables all attribute types
enableAllClassDependencies() - Method in class weka.core.Capabilities: enables all class type dependencies
enableAllClasses() - Method in class weka.core.Capabilities: enables all class types
enableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: enables the dependency flag for the given capability Enabling NOMINAL_ATTRIBUTES also enables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
enableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: enables the given "not to have" capability.
enclosureCharactersTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
entropicAutoBlendTipText() - Method in class weka.classifiers.lazy.KStar: Returns the tip text for this property
ENTROPY - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
entropy(double[]) - Static method in class weka.core.ContingencyTables: Computes the entropy of the given array.
EntropyBasedSplitCrit - Class in weka.classifiers.trees.j48: "Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropyBasedSplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropyBasedSplitCrit
entropyConditionedOnColumns(double[][]) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the rows given the columns.
entropyConditionedOnRows(double[][]) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the columns given the rows.
entropyConditionedOnRows(double[][], double[][], double) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
entropyGain() - Method in class weka.classifiers.trees.lmt.ResidualSplit: Computes entropy gain for current split.
entropyOverColumns(double[][]) - Static method in class weka.core.ContingencyTables: Computes the columns' entropy for the given contingency table.
entropyOverRows(double[][]) - Static method in class weka.core.ContingencyTables: Computes the rows' entropy for the given contingency table.
EntropySplitCrit - Class in weka.classifiers.trees.j48: Class for computing the entropy for a given distribution.
EntropySplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropySplitCrit
enumerateAttributes() - Method in class weka.core.AbstractInstance: Returns an enumeration of all the attributes.
enumerateAttributes() - Method in interface weka.core.Instance: Returns an enumeration of all the attributes.
enumerateAttributes() - Method in class weka.core.Instances: Returns an enumeration of all the attributes.
enumerateColNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
enumerateInstances() - Method in class weka.core.Instances: Returns an enumeration of all instances in the dataset.
enumerateMeasures() - Method in class weka.classifiers.bayes.BayesNet: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.functions.SimpleLogistic: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.functions.SMOreg: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.lazy.IBk: Returns an enumeration of the additional measure names produced by the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
enumerateMeasures() - Method in class weka.classifiers.lazy.LWL: Returns an enumeration of the additional measure names produced by the neighbour search algorithm.
enumerateMeasures() - Method in class weka.classifiers.meta.AdditiveRegression: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.Bagging: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.DecisionTable: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.JRip: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.PART: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.J48: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.LMT: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.m5.M5Base: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.RandomForest: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.trees.REPTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in interface weka.core.AdditionalMeasureProducer: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.BallTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.CoverTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.KDTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.PerformanceStats: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.experiment.AveragingResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures() - Method in class weka.experiment.CrossValidationResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.DatabaseResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator.
enumerateMeasures() - Method in class weka.experiment.LearningRateResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.RandomSplitResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.RegressionSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateRequests() - Method in class weka.gui.beans.Associator: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.AttributeSummarizer: Return an enumeration of actions that the user can ask this bean to perform
enumerateRequests() - Method in class weka.gui.beans.Classifier: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.Clusterer: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.CostBenefitAnalysis
enumerateRequests() - Method in class weka.gui.beans.CrossValidationFoldMaker: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.DataVisualizer: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.Filter: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.GraphViewer: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.ImageViewer
enumerateRequests() - Method in class weka.gui.beans.MetaBean: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ModelPerformanceChart: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.StripChart: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.TextViewer: Get a list of user requests
enumerateRequests() - Method in class weka.gui.beans.TrainTestSplitMaker: Get list of user requests
enumerateRequests() - Method in interface weka.gui.beans.UserRequestAcceptor: Get a list of performable requests
enumerateRowNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
enumerateValues() - Method in class weka.core.Attribute: Returns an enumeration of all the attribute's values if the attribute is nominal, string, or relation-valued, null otherwise.
enumToVector(Enumeration<Option>) - Method in class weka.datagenerators.DataGenerator: Convenience method.
Environment - Class in weka.core: This class encapsulates a map of all environment and java system properties.
Environment() - Constructor for class weka.core.Environment
EnvironmentField - Class in weka.gui.beans: Widget that displays a label and a combo box for selecting environment variables.
EnvironmentField() - Constructor for class weka.gui.beans.EnvironmentField: Construct an EnvironmentField with no label.
EnvironmentField(Environment) - Constructor for class weka.gui.beans.EnvironmentField: Construct an EnvironmentField with no label.
EnvironmentField(String, Environment) - Constructor for class weka.gui.beans.EnvironmentField: Constructor.
EnvironmentField(String) - Constructor for class weka.gui.beans.EnvironmentField: Constructor.
EnvironmentField.WideComboBox - Class in weka.gui.beans: Combo box that allows the drop-down list to be wider than the component itself.
EnvironmentField.WideComboBox() - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox
EnvironmentField.WideComboBox(Object[]) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox
EnvironmentField.WideComboBox(Vector<Object>) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox
EnvironmentField.WideComboBox(ComboBoxModel) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox
EnvironmentHandler - Interface in weka.core: Interface for something that can utilize environment variables.
EOF - Static variable in interface weka.core.json.sym
EOF - Static variable in interface weka.core.mathematicalexpression.sym
EOF - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
EOF_sym() - Method in class weka.core.json.Parser: EOF Symbol index.
EOF_sym() - Method in class weka.core.mathematicalexpression.Parser: EOF Symbol index.
EOF_sym() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser: EOF Symbol index.
EPANECHNIKOV - Static variable in class weka.classifiers.lazy.LWL
epochsTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
epochsTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
EPSILON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
EPSILON_INSENSITIVE - Static variable in class weka.classifiers.functions.SGD: The epsilon insensitive loss function
epsilonParameterTipText() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns the tip text for this property
EQ - Static variable in interface weka.core.mathematicalexpression.sym
eq(double, double) - Static method in class weka.core.Utils: Tests if a is equal to b.
EQ - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
equalCondset(Object) - Method in class weka.associations.LabeledItemSet: Compares two item sets
equalHeaders(Instance) - Method in class weka.core.AbstractInstance: Tests if the headers of two instances are equivalent.
equalHeaders(Instance) - Method in interface weka.core.Instance: Tests if the headers of two instances are equivalent.
equalHeaders(Instances) - Method in class weka.core.Instances: Checks if two headers are equivalent.
equalHeadersMsg(Instance) - Method in class weka.core.AbstractInstance: Checks if the headers of two instances are equivalent.
equalHeadersMsg(Instance) - Method in interface weka.core.Instance: Checks if the headers of two instances are equivalent.
equalHeadersMsg(Instances) - Method in class weka.core.Instances: Checks if two headers are equivalent.
equals(Object) - Method in class weka.associations.AssociationRule: Return true if this rule is equal to the supplied one.
equals(Object) - Method in class weka.associations.AssociatorEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.associations.BinaryItem: Equals.
equals(Object) - Method in class weka.associations.Item: Equals.
equals(Object) - Method in class weka.associations.ItemSet: Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.LabeledItemSet: Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.NominalItem: Equals.
equals(Object) - Method in class weka.associations.NumericItem: Equals.
equals(Object) - Method in class weka.classifiers.Evaluation: Tests whether the current evaluation object is equal to another evaluation object.
equals(Object) - Method in class weka.classifiers.evaluation.Evaluation: Tests whether the current evaluation object is equal to another evaluation object.
equals(Object) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.classifiers.rules.DecisionTableHashKey: Tests if two instances are equal
equals(Object) - Method in class weka.clusterers.ClusterEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.core.Attribute: Tests if given attribute is equal to this attribute.
equals(Object) - Method in class weka.core.AttributeLocator: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class weka.core.ClassDiscovery.StringCompare: Indicates whether some other object is "equal to" this Comparator.
equals(Object) - Method in class weka.core.SelectedTag: Returns true if this SelectedTag equals another object
equals(Object) - Method in class weka.core.SerializedObject
equals(Object) - Method in class weka.core.Trie: Compares the specified object with this collection for equality.
equals(Object) - Method in class weka.core.Trie.TrieNode: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class weka.core.Version: whether the given version string is equal to this version
equals(Object) - Method in class weka.estimators.Estimator: Tests whether the current estimation object is equal to another estimation object
equals(Object) - Method in class weka.gui.graphvisualizer.GraphEdge
equals(Object) - Method in class weka.gui.graphvisualizer.GraphNode: Returns true if passed in argument is an instance of GraphNode and is equal to this node.
equals(Object) - Method in class weka.gui.SortedTableModel.SortContainer: Indicates whether some other object is "equal to" this one.
equalsMsg(Object) - Method in class weka.core.Attribute: Tests if given attribute is equal to this attribute.
equalTo(Test) - Method in class weka.datagenerators.Test: Compares the test with the test that is given as parameter.
errms(StreamTokenizer, String) - Static method in class weka.core.converters.ConverterUtils: Throws error message with line number and last token read.
errms(StreamTokenizer, String) - Static method in class weka.core.converters.StreamTokenizerUtils: Throws error message with line number and last token read.
error() - Method in class weka.classifiers.evaluation.NumericPrediction: Calculates the prediction error.
error - Static variable in interface weka.core.json.sym
error - Static variable in interface weka.core.mathematicalexpression.sym
error - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
ERROR_SHAPE - Static variable in class weka.gui.visualize.Plot2D
error_sym() - Method in class weka.core.json.Parser: error Symbol index.
error_sym() - Method in class weka.core.mathematicalexpression.Parser: error Symbol index.
error_sym() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser: error Symbol index.
ErrorBasedMeritEvaluator - Interface in weka.attributeSelection: Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
errorFunction(double) - Static method in class weka.core.Statistics: Returns the error function of the normal distribution.
errorFunctionComplemented(double) - Static method in class weka.core.Statistics: Returns the complementary Error function of the normal distribution.
errorOnProbabilitiesTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
errorOnProbabilitiesTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
errorPlotPointSizeProportionalToMarginTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
errorRate() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Returns the estimated error rate.
errorRate() - Method in class weka.classifiers.Evaluation: Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorRate() - Method in class weka.classifiers.evaluation.Evaluation: Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit: This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod: This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit: This function calculates what the error value should be.
ErrorVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier errors in the explorer.
escapeQuote(String) - Method in class weka.gui.scripting.SyntaxDocument: Escapes the quote delimiter.
establishCacheIfNeeded(PrintStream...) - Static method in class weka.core.WekaPackageManager: Establish the local copy of the package meta data if needed
estimate(double[][], double[]) - Method in interface weka.estimators.MultivariateEstimator: Fits the value to the density estimator.
estimate(double[][], double[]) - Method in class weka.estimators.MultivariateGaussianEstimator
estimateCPTs() - Method in class weka.classifiers.bayes.BayesNet: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
Estimator - Class in weka.estimators: Abstract class for all estimators.
Estimator() - Constructor for class weka.estimators.Estimator
ESTIMATOR_HISTOGRAM - Static variable in class weka.classifiers.meta.RegressionByDiscretization: Use histogram estimator
ESTIMATOR_KERNEL - Static variable in class weka.classifiers.meta.RegressionByDiscretization: filter: Standardize training data
ESTIMATOR_NORMAL - Static variable in class weka.classifiers.meta.RegressionByDiscretization: filter: No normalization/standardization
estimatorTipText() - Method in class weka.classifiers.bayes.BayesNet: This will return a string describing the BayesNetEstimator.
estimatorTypeTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
EstimatorUtils - Class in weka.estimators: Contains static utility functions for Estimators.
EstimatorUtils() - Constructor for class weka.estimators.EstimatorUtils
ETable - Class in weka.gui: A better-looking table than JTable.
ETable() - Constructor for class weka.gui.ETable
Euclidean - Class in weka.core.pmml.jaxbbindings: Java class for euclidean element declaration.
Euclidean() - Constructor for class weka.core.pmml.jaxbbindings.Euclidean
EuclideanDistance - Class in weka.core: Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.
EuclideanDistance() - Constructor for class weka.core.EuclideanDistance: Constructs an Euclidean Distance object, Instances must be still set.
EuclideanDistance(Instances) - Constructor for class weka.core.EuclideanDistance: Constructs an Euclidean Distance object and automatically initializes the ranges.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.CachedKernel: Implements the abstract function of Kernel using the cache.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.Kernel: Computes the result of the kernel function for two instances.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Computes the result of the kernel function for two instances.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.StringKernel: Computes the result of the kernel function for two instances.
EVAL_ACCURACY - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_ACCURACY - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_AUC - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_AUC - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_AUPRC - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_DEFAULT - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_DEFAULT - Static variable in class weka.classifiers.rules.DecisionTable: default is accuracy for discrete class and RMSE for numeric class
EVAL_FMEASURE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_MAE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_MAE - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_RMSE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_RMSE - Static variable in class weka.classifiers.rules.DecisionTable
evalBoolean(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the boolean result of the XPath expression.
evalDouble(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the double result of the XPath expression.
evalString(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the boolean result of the XPath expression.
evaluate(String, String[]) - Static method in class weka.associations.AssociatorEvaluation: Evaluates an associator with the options given in an array of strings.
evaluate(Associator, String[]) - Static method in class weka.associations.AssociatorEvaluation: Evaluates the associator with the given commandline options and returns the evaluation string.
evaluate(Associator, Instances) - Method in class weka.associations.AssociatorEvaluation: Evaluates the associator with the given commandline options and returns the evaluation string.
evaluate(Kernel, String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates the Kernel with the given commandline options and returns the evaluation string.
evaluate(String, String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates a kernel with the options given in an array of strings.
evaluate(Kernel, Instances) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates the Kernel with the given commandline options and returns the evaluation string.
evaluate(String, HashMap<String, Double>) - Static method in class weka.core.MathematicalExpression: Parses and evaluates the given expression.
evaluateAttribute(int) - Method in interface weka.attributeSelection.AttributeEvaluator: evaluates an individual attribute
evaluateAttribute(int) - Method in class weka.attributeSelection.AttributeSetEvaluator: evaluates an individual attribute
evaluateAttribute(int[], int[]) - Method in class weka.attributeSelection.AttributeSetEvaluator: Evaluates a set of attributes
evaluateAttribute(int) - Method in class weka.attributeSelection.CorrelationAttributeEval: Evaluates an individual attribute by measuring the correlation (Pearson's) between it and the class.
evaluateAttribute(int) - Method in class weka.attributeSelection.GainRatioAttributeEval: evaluates an individual attribute by measuring the gain ratio of the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.InfoGainAttributeEval: evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.OneRAttributeEval: evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.PrincipalComponents: Evaluates the merit of a transformed attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Evaluates an individual attribute using ReliefF's instance based approach.
evaluateAttribute(int) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: evaluates an individual attribute by measuring the symmetrical uncertainty between it and the class.
evaluateClusterer(Instances) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Instances, String) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Instances, String, boolean) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Clusterer, String[]) - Static method in class weka.clusterers.ClusterEvaluation: Evaluates a clusterer with the options given in an array of strings.
evaluateExpression(Instance) - Method in class weka.core.AttributeExpression: Evaluate the expression using the supplied Instance.
evaluateExpression(double[]) - Method in class weka.core.AttributeExpression: Evaluate the expression using the supplied array of attribute values.
evaluateModel(String, String[]) - Static method in class weka.classifiers.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a given set of instances.
evaluateModel(String, String[]) - Static method in class weka.classifiers.evaluation.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.evaluation.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a given set of instances.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied prediction on a single instance.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied prediction on a single instance.
evaluateModelOnceAndRecordPrediction(Classifier, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a single instance and records the prediction.
evaluateModelOnceAndRecordPrediction(double[], Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnceAndRecordPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a single instance and records the prediction.
evaluateModelOnceAndRecordPrediction(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.GiniSplitMetric
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.InfoGainSplitMetric
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.SplitMetric: Evaluate the merit of a split
evaluateSubset(BitSet) - Method in class weka.attributeSelection.CfsSubsetEval: evaluates a subset of attributes
evaluateSubset(BitSet, Instances) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator: Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instance, boolean) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator: Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet) - Method in interface weka.attributeSelection.SubsetEvaluator: evaluates a subset of attributes
evaluateSubset(BitSet) - Method in class weka.attributeSelection.WrapperSubsetEval: Evaluates a subset of attributes
Evaluation - Class in weka.classifiers: Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.Evaluation
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.Evaluation
Evaluation - Class in weka.classifiers.evaluation: Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.evaluation.Evaluation: Initializes all the counters for the evaluation.
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.Evaluation: Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
evaluationForSingleInstance(double[], Instance, boolean) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluationForSingleInstance(double[], Instance, boolean) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluationMeasureTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
evaluationMeasureTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
EvaluationMetricHelper - Class in weka.classifiers.evaluation: Helper routines for extracting metric values from built-in and plugin evaluation metrics.
EvaluationMetricHelper(Evaluation) - Constructor for class weka.classifiers.evaluation.EvaluationMetricHelper: Construct a new EvaluationMetricHelper
EvaluationMetricSelectionDialog - Class in weka.gui: A GUI dialog for selecting classification/regression evaluation metrics to be output.
EvaluationMetricSelectionDialog(Dialog, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
EvaluationMetricSelectionDialog(Window, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
EvaluationMetricSelectionDialog(Frame, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
evaluationMetricsToOutputTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
evaluationMetricTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
EvaluationUtils - Class in weka.classifiers.evaluation: Contains utility functions for generating lists of predictions in various manners.
EvaluationUtils() - Constructor for class weka.classifiers.evaluation.EvaluationUtils
evaluatorTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the tip text for this property
evaluatorTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns the tip text for this property
evalUsingTrainingDataTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
EventConstraints - Interface in weka.gui.beans: Interface for objects that want to be able to specify at any given time whether their current configuration allows a particular event to be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Appender: Returns true if, at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Associator: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Associator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassAssigner: Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Classifier: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Classifier: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassValuePicker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Clusterer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.CrossValidationFoldMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.DataVisualizer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in interface weka.gui.beans.EventConstraints: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Filter: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.FlowByExpression
eventGeneratable(String) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Join
eventGeneratable(String) - Method in class weka.gui.beans.Loader: Returns true if the named event can be generated at this time
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.MetaBean: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.PredictionAppender: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Sorter: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TestSetMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TextViewer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainingSetMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainTestSplitMaker: Returns true, if at the current time, the named event could be generated.
EventValues - Class in weka.core.pmml.jaxbbindings: Java class for EventValues element declaration.
EventValues() - Constructor for class weka.core.pmml.jaxbbindings.EventValues
execute() - Method in class weka.classifiers.CheckSource: performs the comparison test
execute(String) - Method in class weka.experiment.DatabaseUtils: Executes a SQL query.
execute() - Method in class weka.experiment.RemoteExperimentSubTask: Run the experiment
execute() - Method in interface weka.experiment.Task: Execute this task.
execute() - Method in class weka.filters.CheckSource: performs the comparison test
execute() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Perform the sub task
execute() - Method in class weka.gui.explorer.DataGeneratorPanel: generates the instances, returns TRUE if successful
execute() - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor and stores it
execute(boolean) - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor
execute(boolean, boolean) - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor and stores it only if the the param store is TRUE.
execute() - Method in class weka.gui.sql.QueryPanel: executes the current query.
executeTask(Task) - Method in interface weka.experiment.Compute: Execute a task
executeTask(Task) - Method in class weka.experiment.RemoteEngine: Takes a task object and queues it for execution
executionSlotsTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
exists(TechnicalInformation.Field) - Method in class weka.core.TechnicalInformation: returns TRUE if the field is stored and has a value different from the empty string.
EXP - Static variable in interface weka.core.mathematicalexpression.sym
EXP - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
EXP_INDEX_TABLE - Static variable in class weka.experiment.DatabaseUtils: The name of the table containing the index to experiments.
EXP_RESULT_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the results table name.
EXP_RESULT_PREFIX - Static variable in class weka.experiment.DatabaseUtils: The prefix for result table names.
EXP_SETUP_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the experiment setup (parameters).
EXP_TYPE_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the experiment type (ResultProducer).
expectedCosts(double[]) - Method in class weka.classifiers.CostMatrix: Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedCosts(double[], Instance) - Method in class weka.classifiers.CostMatrix: Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedResultsPerAverageTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
Experiment - Class in weka.experiment: Holds all the necessary configuration information for a standard type experiment.
Experiment() - Constructor for class weka.experiment.Experiment
Experimenter - Class in weka.gui.experiment: The main class for the experiment environment.
Experimenter(boolean) - Constructor for class weka.gui.experiment.Experimenter: Creates the experiment environment gui with no initial experiment
ExperimenterDefaults - Class in weka.gui.experiment: This class offers get methods for the default Experimenter settings in the props file weka/gui/experiment/Experimenter.props.
ExperimenterDefaults() - Constructor for class weka.gui.experiment.ExperimenterDefaults
experimentIndexExists() - Method in class weka.experiment.DatabaseUtils: Returns true if the experiment index exists.
ExplicitTestsetResultProducer - Class in weka.experiment: Loads the external test set and calls the appropriate SplitEvaluator to generate some results.
The filename of the test set is constructed as follows:
<dir> + / + <prefix> + <relation-name> + <suffix>
The relation-name can be modified by using the regular expression to replace the matching sub-string with a specified replacement string.
ExplicitTestsetResultProducer() - Constructor for class weka.experiment.ExplicitTestsetResultProducer
Explorer - Class in weka.gui.explorer: The main class for the Weka explorer.
Explorer() - Constructor for class weka.gui.explorer.Explorer: Creates the experiment environment gui with no initial experiment
Explorer.CapabilitiesFilterChangeEvent - Class in weka.gui.explorer: This event can be fired in case the capabilities filter got changed
Explorer.CapabilitiesFilterChangeEvent(Object, Capabilities) - Constructor for class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent: Constructs a GOECapabilitiesFilterChangeEvent object.
Explorer.CapabilitiesFilterChangeListener - Interface in weka.gui.explorer: Interface for classes that listen for filter changes.
Explorer.ExplorerPanel - Interface in weka.gui.explorer: A common interface for panels to be displayed in the Explorer
Explorer.LogHandler - Interface in weka.gui.explorer: A common interface for panels in the explorer that can handle logs
ExplorerDefaults - Class in weka.gui.explorer: This class offers get methods for the default Explorer settings in the props file weka/gui/explorer/Explorer.props.
ExplorerDefaults() - Constructor for class weka.gui.explorer.ExplorerDefaults
ExponentialFormat - Class in weka.core.matrix
ExponentialFormat() - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int, boolean) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int, int, boolean, boolean) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialSmoothing - Class in weka.core.pmml.jaxbbindings: Java class for ExponentialSmoothing element declaration.
ExponentialSmoothing() - Constructor for class weka.core.pmml.jaxbbindings.ExponentialSmoothing
exponentTipText() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the tip text for this property
exponentTipText() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the tip text for this property
Expression - Class in weka.core.pmml
Expression(FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Expression
Expression - Class in weka.datagenerators.classifiers.regression: A data generator for generating y according to a given expression out of randomly generated x.
E.g., the mexican hat can be generated like this:
sin(abs(a1)) / abs(a1)
In addition to this function, the amplitude can be changed and gaussian noise can be added.
Expression() - Constructor for class weka.datagenerators.classifiers.regression.Expression: initializes the generator
expressionTipText() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the tip text for this property.
expressionTipText() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the tip text for this property.
Extension - Class in weka.core.pmml.jaxbbindings: Java class for Extension element declaration.
Extension() - Constructor for class weka.core.pmml.jaxbbindings.Extension
ExtensionFileFilter - Class in weka.gui: Provides a file filter for FileChoosers that accepts or rejects files based on their extension.
ExtensionFileFilter(String, String) - Constructor for class weka.gui.ExtensionFileFilter: Creates the ExtensionFileFilter
ExtensionFileFilter(String[], String) - Constructor for class weka.gui.ExtensionFileFilter: Creates an ExtensionFileFilter that accepts files that have any of the extensions contained in the supplied array.
extraArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: Count nr of exta arcs from other network compared to current network Note that an arc is not 'extra' if it is reversed.
extract(RevisionHandler) - Static method in class weka.core.RevisionUtils: Extracts the revision string returned by the RevisionHandler.
extract(String) - Static method in class weka.core.RevisionUtils: Extracts the revision string.
extremeValuesAsOutliersTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
extremeValuesFactorTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property

F

FactorList - Class in weka.core.pmml.jaxbbindings: Java class for FactorList element declaration.
FactorList() - Constructor for class weka.core.pmml.jaxbbindings.FactorList
FAILED - Static variable in class weka.experiment.TaskStatusInfo
failed() - Method in class weka.gui.sql.event.ConnectionEvent: whether an exception happened and is stored
failed() - Method in class weka.gui.sql.event.QueryExecuteEvent: is TRUE in case the exception is not NULL, i.e.
FALLOUT_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Fallout
FALSE - Static variable in interface weka.core.mathematicalexpression.sym
False - Class in weka.core.pmml.jaxbbindings: Java class for False element declaration.
False() - Constructor for class weka.core.pmml.jaxbbindings.False
FALSE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
FALSE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Negatives
FALSE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Positives
falseNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false negative rate with respect to a particular class.
falseNegativeRate(int) - Method in class weka.classifiers.Evaluation: Calculate the false negative rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false positive rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.Evaluation: Calculate the false positive rate with respect to a particular class.
FARTHEST_FIRST - Static variable in class weka.clusterers.SimpleKMeans
FarthestFirst - Class in weka.clusterers: Cluster data using the FarthestFirst algorithm.

For more information see:

Hochbaum, Shmoys (1985).
FarthestFirst() - Constructor for class weka.clusterers.FarthestFirst
fastDistanceCalcTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
fastRegressionTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
FastVector<E> - Class in weka.core: Deprecated.
FastVector() - Constructor for class weka.core.FastVector: Deprecated. Constructs an empty vector with initial capacity zero.
FastVector(int) - Constructor for class weka.core.FastVector: Deprecated. Constructs a vector with the given capacity.
FieldColumnPair - Class in weka.core.pmml.jaxbbindings: Java class for FieldColumnPair element declaration.
FieldColumnPair() - Constructor for class weka.core.pmml.jaxbbindings.FieldColumnPair
FieldMetaInfo - Class in weka.core.pmml: Abstract superclass for various types of field meta data.
FieldMetaInfo(Element) - Constructor for class weka.core.pmml.FieldMetaInfo: Construct a new FieldMetaInfo.
FieldMetaInfo.Interval - Class in weka.core.pmml: Inner class for an Interval.
FieldMetaInfo.Interval.Closure - Enum in weka.core.pmml: Enumerated type for the closure.
FieldMetaInfo.Optype - Enum in weka.core.pmml: Enumerated type for the Optype
FieldMetaInfo.Value - Class in weka.core.pmml: Inner class for Values
FieldMetaInfo.Value.Property - Enum in weka.core.pmml: Enumerated type for the property.
FieldRef - Class in weka.core.pmml: Class encapsulating a FieldRef Expression.
FieldRef(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.FieldRef
FieldRef - Class in weka.core.pmml.jaxbbindings: Java class for FieldRef element declaration.
FieldRef() - Constructor for class weka.core.pmml.jaxbbindings.FieldRef
fields() - Method in class weka.core.TechnicalInformation: returns an enumeration over all the stored fields
fieldSeparatorTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
fieldSeparatorTipText() - Method in class weka.core.converters.CSVSaver: Returns the tip text for this property.
FIELDUSAGETYPE - Enum in weka.core.pmml.jaxbbindings: Java class for FIELD-USAGE-TYPE.
FieldValue - Class in weka.core.pmml.jaxbbindings: Java class for FieldValue element declaration.
FieldValue() - Constructor for class weka.core.pmml.jaxbbindings.FieldValue
FieldValueCount - Class in weka.core.pmml.jaxbbindings: Java class for FieldValueCount element declaration.
FieldValueCount() - Constructor for class weka.core.pmml.jaxbbindings.FieldValueCount
FILE_EXTENSION - Static variable in class weka.classifiers.CostMatrix: The deafult file extension for cost matrix files
FILE_EXTENSION - Static variable in class weka.core.converters.ArffLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.C45Loader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.CSVLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.JSONLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.LibSVMLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.LibSVMSaver: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.MatlabLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.MatlabSaver: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.SerializedInstancesLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.SVMLightLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.SVMLightSaver: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.XRFFLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.Instances: The filename extension that should be used for arff files
FILE_EXTENSION - Static variable in class weka.core.xml.KOML: the extension for KOML files (including '.')
FILE_EXTENSION - Static variable in class weka.core.xml.XMLInstances: The filename extension that should be used for xrff files
FILE_EXTENSION - Static variable in class weka.core.xml.XStream: the extension for XStream files (including '.')
FILE_EXTENSION - Static variable in class weka.experiment.Experiment: The filename extension that should be used for experiment files
FILE_EXTENSION - Static variable in class weka.gui.beans.Classifier: the extension for serialized models (binary Java serialization)
FILE_EXTENSION - Static variable in class weka.gui.beans.KnowledgeFlowApp: the extension for the serialized setups (Java serialization)
FILE_EXTENSION - Static variable in class weka.gui.beans.SerializedModelSaver: the extension for serialized models (binary Java serialization)
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.AbstractFileLoader: the extension for compressed files
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.ArffLoader
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.JSONLoader: the extension for compressed files.
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.XRFFLoader: the extension for compressed files
FILE_EXTENSION_XML - Static variable in class weka.gui.beans.KnowledgeFlowApp: the extension for the serialized setups (Java serialization)
FileEditor - Class in weka.gui: A PropertyEditor for File objects that lets the user select a file.
FileEditor() - Constructor for class weka.gui.FileEditor
FileEnvironmentField - Class in weka.gui.beans: Widget that displays a label, editable combo box for selecting environment variables and a button for brining up a file browser.
FileEnvironmentField() - Constructor for class weka.gui.beans.FileEnvironmentField: Constructor
FileEnvironmentField(Environment) - Constructor for class weka.gui.beans.FileEnvironmentField: Constructor
FileEnvironmentField(String, Environment) - Constructor for class weka.gui.beans.FileEnvironmentField
FileEnvironmentField(String, Environment, int) - Constructor for class weka.gui.beans.FileEnvironmentField: Constructor
FileEnvironmentField(String, Environment, int, boolean) - Constructor for class weka.gui.beans.FileEnvironmentField: Constructor
FileEnvironmentField(String, int, boolean) - Constructor for class weka.gui.beans.FileEnvironmentField: Constructor
FileLogger - Class in weka.core.logging: A simple file logger, that just logs to a single file.
FileLogger() - Constructor for class weka.core.logging.FileLogger
filePrefix() - Method in class weka.core.converters.AbstractFileSaver: Gets the file name prefix
filePrefix() - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
filePrefix() - Method in interface weka.core.converters.Saver: Gets the file prefix This method is used in the KnowledgeFlow GUI.
FileScriptingPanel - Class in weka.gui.scripting: Supports loading/saving of files.
FileScriptingPanel() - Constructor for class weka.gui.scripting.FileScriptingPanel
FileScriptingPanel.BasicAction - Class in weka.gui.scripting: A slightly extended action class.
FileScriptingPanel.BasicAction(String, String, String, Character) - Constructor for class weka.gui.scripting.FileScriptingPanel.BasicAction: Constructor for setting up an action.
FileSourcedConverter - Interface in weka.core.converters: Interface to a loader/saver that loads/saves from a file source.
fill(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
fill3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle with 3D effect in current pen color.
fillArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillFrame(Component) - Method in interface weka.gui.MainMenuExtension: Fills the frame with life, like adding components, window listeners, setting size, location, etc.
fillIn(int[], boolean[][]) - Method in class weka.classifiers.bayes.net.MarginCalculator: Apply Tarjan and Yannakakis (1984) fill in algorithm for graph triangulation.
fillOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled Oval in current pen color.
fillPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillPolygon(Polygon) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle in current pen color.
fillRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillWithMissingTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
Filter - Class in weka.filters: An abstract class for instance filters: objects that take instances as input, carry out some transformation on the instance and then output the instance.
Filter() - Constructor for class weka.filters.Filter
filter(String, Instances) - Static method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser: Filters the input dataset against the provided expression.
Filter - Class in weka.gui.beans: A wrapper bean for Weka filters
Filter() - Constructor for class weka.gui.beans.Filter
FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcesses: no filter
FILTER_NONE - Static variable in class weka.classifiers.functions.SMO: filter: No normalization/standardization
FILTER_NONE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: None
FILTER_NONE - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: No normalization.
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcesses: normalizes the data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMO: filter: Normalize training data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: Normalzie
FILTER_NORMALIZE_ALL - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: Normalize all data.
FILTER_NORMALIZE_TEST_ONLY - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: Normalize test data only.
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcesses: standardizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMO: filter: Standardize training data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: Standardize
filterAfterFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the tip text for this property.
FilterBeanInfo - Class in weka.gui.beans: Bean info class for the Filter bean
FilterBeanInfo() - Constructor for class weka.gui.beans.FilterBeanInfo
FilterCustomizer - Class in weka.gui.beans: GUI customizer for the filter bean
FilterCustomizer() - Constructor for class weka.gui.beans.FilterCustomizer
FilteredAssociationRules - Class in weka.associations: Class encapsulating a list of association rules and the preprocessing filter that was applied before they were generated.
FilteredAssociationRules(String, Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociationRules(Object, Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociationRules(Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociator - Class in weka.associations: Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
FilteredAssociator() - Constructor for class weka.associations.FilteredAssociator: Default constructor.
FilteredClassifier - Class in weka.classifiers.meta: Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
FilteredClassifier() - Constructor for class weka.classifiers.meta.FilteredClassifier: Default constructor.
FilteredClusterer - Class in weka.clusterers: Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter.
FilteredClusterer() - Constructor for class weka.clusterers.FilteredClusterer: Default constructor.
filterFile(Filter, String[]) - Static method in class weka.filters.Filter: Method for testing filters.
filtersTipText() - Method in class weka.filters.MultiFilter: Returns the tip text for this property
filtersTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns the tip text for this property.
filterTipText() - Method in class weka.associations.FilteredAssociator: Returns the tip text for this property
filterTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the tip text for this property
filterTipText() - Method in class weka.clusterers.FilteredClusterer: Returns the tip text for this property.
filterTypeTipText() - Method in class weka.classifiers.functions.GaussianProcesses: Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
finalize() - Method in class weka.gui.sql.ResultSetTable: frees up the memory
finalize() - Method in class weka.gui.sql.ResultSetTableModel: frees up the memory.
finalize() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
finalizeAggregation() - Method in class weka.classifiers.bayes.NaiveBayes
finalizeAggregation() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
finalizeAggregation() - Method in class weka.classifiers.evaluation.AggregateableEvaluation
finalizeAggregation() - Method in class weka.classifiers.functions.Logistic: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.functions.SGD: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.functions.SGDText: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.meta.Bagging: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.meta.Vote: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.trees.RandomForest
finalizeAggregation() - Method in interface weka.core.Aggregateable: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.estimators.DiscreteEstimator
finalizeAggregation() - Method in class weka.estimators.KernelEstimator
finalizeAggregation() - Method in class weka.estimators.NormalEstimator
find(String) - Method in class weka.core.ClassCache: Find all classes that have the supplied matchText String in their suffix.
find(String, String[]) - Static method in class weka.core.ClassDiscovery: Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(String, String) - Static method in class weka.core.ClassDiscovery: Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(Class<?>, String[]) - Static method in class weka.core.ClassDiscovery: Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(String) - Static method in class weka.core.ClassDiscovery: Find all classes that have the supplied matchText String in their suffix.
find(Class<?>, String) - Static method in class weka.core.ClassDiscovery: Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find() - Method in class weka.core.FindWithCapabilities: returns a list with all the classnames that fit the criteria.
find(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath: returns the property and object associated with the given path, null if a problem occurred.
find(String) - Method in class weka.core.Trie.TrieNode: returns the node with the given suffix
findAllRulesForSupportLevelTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
findArgmin(double[], double[][]) - Method in class weka.core.ConjugateGradientOptimization: Main algorithm.
findArgmin(double[], double[][]) - Method in class weka.core.Optimization: Main algorithm.
findBestLeaf(double[], RuleNode[]) - Method in class weka.classifiers.trees.m5.RuleNode: Find the leaf with greatest coverage
findCentralTendencies(double[]) - Method in class weka.classifiers.BVDecomposeSegCVSub: Finds the central tendency, given the classifications for an instance.
findInstance(String, Integer...) - Static method in class weka.gui.beans.BeanInstance: Search for a named bean in the indexed flow
findInstance(Point, Integer...) - Static method in class weka.gui.beans.BeanInstance: Looks for a bean (if any) whose bounds contain the supplied point
findInstances(Rectangle, Integer...) - Static method in class weka.gui.beans.BeanInstance: Looks for all beans (if any) located within the supplied bounding box.
findMinDistance(Instances, int) - Static method in class weka.estimators.EstimatorUtils: Find the minimum distance between values
findNodes(String) - Method in class weka.core.xml.XMLDocument: Returns the nodes that the given xpath expression will find in the document.
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
findPackages() - Static method in class weka.core.ClassDiscovery: Lists all packages it can find in the classpath.
findReadMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler: returns the method with the given name that has the same signature as readFromXML() of the XMLSerialiation class.
findSchemeMatch(Class<?>, String, boolean, boolean) - Static method in class weka.Run: Find a scheme that matches the supplied suffix
findSchemeMatch(String, boolean) - Static method in class weka.Run: Find a scheme that matches the supplied suffix
findTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
FindWithCapabilities - Class in weka.core: Locates all classes with certain capabilities.
FindWithCapabilities() - Constructor for class weka.core.FindWithCapabilities
findWriteMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler: returns the method with the given name that has the same signature as writeToXML() of the XMLSerialiation class.
FINE - Static variable in class weka.core.Debug: the log level Fine
FINER - Static variable in class weka.core.Debug: the log level Finer
FINEST - Static variable in class weka.core.Debug: the log level Finest
finished() - Method in class weka.experiment.OutputZipper: Closes the zip file.
FINISHED - Static variable in class weka.experiment.TaskStatusInfo
finished(Logger) - Method in class weka.gui.beans.StreamThroughput: Register the end of measurement.
finished() - Method in class weka.gui.beans.StreamThroughput: Register the end of measurement.
finished() - Method in class weka.gui.visualize.PostscriptGraphics: Finalizes output file.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Fires a LayoutCompleteEvent.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This fires a LayoutCompleteEvent once a layout has been completed.
FIRST - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner: use the first attribute as class.
firstElement() - Method in class weka.core.FastVector: Deprecated. Returns the first element of the vector.
firstElement() - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the first component of this list.
firstInstance() - Method in class weka.core.Instances: Returns the first instance in the set.
FirstOrder - Class in weka.filters.unsupervised.attribute: This instance filter takes a range of N numeric attributes and replaces them with N-1 numeric attributes, the values of which are the difference between consecutive attribute values from the original instance.
FirstOrder() - Constructor for class weka.filters.unsupervised.attribute.FirstOrder
firstValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
firstValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
fitToScreen() - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer: Fits the tree to the current screen size.
fitToScreen() - Method in class weka.gui.treevisualizer.TreeVisualizer: Fits the tree to the current screen size.
FlexibleDecimalFormat - Class in weka.core.matrix
FlexibleDecimalFormat() - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean, boolean, boolean) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(double) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FLOAT - Static variable in class weka.experiment.DatabaseUtils: Type mapping for FLOAT used for reading experiment results.
FloatingPointFormat - Class in weka.core.matrix: Class for the format of floating point numbers
FloatingPointFormat() - Constructor for class weka.core.matrix.FloatingPointFormat: Default constructor
FloatingPointFormat(int) - Constructor for class weka.core.matrix.FloatingPointFormat
FloatingPointFormat(int, int) - Constructor for class weka.core.matrix.FloatingPointFormat
FloatingPointFormat(int, int, boolean) - Constructor for class weka.core.matrix.FloatingPointFormat
FLOOR - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FLOOR - Static variable in interface weka.core.mathematicalexpression.sym
FLOOR - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
FLOOR1 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FlowByExpression - Class in weka.gui.beans: A bean that splits incoming instances (or instance streams) according to the evaluation of a logical expression.
FlowByExpression() - Constructor for class weka.gui.beans.FlowByExpression: Constructor
FlowByExpressionBeanInfo - Class in weka.gui.beans: BeanInfo class for FlowByExpression
FlowByExpressionBeanInfo() - Constructor for class weka.gui.beans.FlowByExpressionBeanInfo
FlowByExpressionCustomizer - Class in weka.gui.beans: Customizer for the FlowByExpression node
FlowByExpressionCustomizer() - Constructor for class weka.gui.beans.FlowByExpressionCustomizer: Constructor
FlowRunner - Class in weka.gui.beans: Small utility class for executing KnowledgeFlow flows outside of the KnowledgeFlow application
FlowRunner() - Constructor for class weka.gui.beans.FlowRunner: Constructor
FlowRunner(boolean, boolean) - Constructor for class weka.gui.beans.FlowRunner
FlowRunner.SimpleLogger - Class in weka.gui.beans
FlowRunner.SimpleLogger() - Constructor for class weka.gui.beans.FlowRunner.SimpleLogger
flush() - Method in class weka.core.logging.OutputLogger.OutputPrintStream: ignored.
flush() - Method in class weka.core.Tee: flushes all the printstreams.
fMeasure(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the F-Measure with respect to a particular class.
fMeasure(int) - Method in class weka.classifiers.Evaluation: Calculate the F-Measure with respect to a particular class.
FMEASURE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: FMeasure
FOLD_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the key field containing the fold number
foldsTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
foldsTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
foldsTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
foldsTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker: Tip text for this property
foldTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the tip text for this property
foldTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the tip text for this property
forCapabilities(Capabilities) - Static method in class weka.core.TestInstances: returns a TestInstances instance setup already for the the given capabilities.
forInstances(Instances) - Static method in class weka.core.Capabilities: returns a Capabilities object specific for this data.
forInstances(Instances, boolean) - Static method in class weka.core.Capabilities: returns a Capabilities object specific for this data.
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.ExponentialFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.FlexibleDecimalFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.FloatingPointFormat
FORMAT_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent
FORMAT_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent: Specifies that the instance format is available
FORMAT_HHMMSS - Static variable in class weka.core.Debug.Clock: the output format in hours:minutes:seconds, with fraction of msecs
FORMAT_MILLISECONDS - Static variable in class weka.core.Debug.Clock: the output format in milli-seconds
FORMAT_SECONDS - Static variable in class weka.core.Debug.Clock: the output format in seconds, with fraction of msecs
formatDate(double) - Method in class weka.core.Attribute: Returns the given amount of milliseconds formatted according to the current Date format.
formatString(String) - Method in class weka.core.matrix.FlexibleDecimalFormat
formatTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
forName(String, String[]) - Static method in class weka.associations.AbstractAssociator: Creates a new instance of a associator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASEvaluation: Creates a new instance of an attribute/subset evaluator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASSearch: Creates a new instance of a search class given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.classifiers.AbstractClassifier: Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.classifiers.functions.supportVector.Kernel: Creates a new instance of a kernel given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.clusterers.AbstractClusterer: Creates a new instance of a clusterer given it's class name and (optional) arguments to pass to it's setOptions method.
forName(Class<?>, String, String[]) - Static method in class weka.core.Utils: Creates a new instance of an object given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.estimators.Estimator: Creates a new instance of a estimatorr given it's class name and (optional) arguments to pass to it's setOptions method.
foundUsefulAttribute() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns true if a usable attribute was found.
foundUsefulAttribute() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Returns true if a usable attribute was found.
FP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Positive Rate"
FPGrowth - Class in weka.associations: Class implementing the FP-growth algorithm for finding large item sets without candidate generation.
FPGrowth() - Constructor for class weka.associations.FPGrowth: Construct a new FPGrowth object.
FProbability(double, int, int) - Static method in class weka.core.Statistics: Computes probability of F-ratio.
freeNotCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule: Free up memory consumed by the set of instances not covered by this rule.
FREQ_ASCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder: The class values are sorted in ascending order based on their frequencies
FREQ_DESCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder: The class values are sorted in descending order based on their frequencies
fromCommandline(String) - Static method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns a fully configured object from the given commandline.
FromFile - Class in weka.classifiers.bayes.net.search.fixed: The FromFile reads the structure of a Bayes net from a file in BIFF format.
FromFile() - Constructor for class weka.classifiers.bayes.net.search.fixed.FromFile
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.GAP
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC
fromXML(Document) - Method in class weka.core.xml.XMLSerialization: returns the given DOM document as an instance of the specified class
fullValue() - Method in class weka.gui.HierarchyPropertyParser: The full value of the current node, i.e.
Function - Class in weka.core.pmml: Abstract superclass for PMML built-in and DefineFunctions.
Function() - Constructor for class weka.core.pmml.Function
FUNCTION_1 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 1
FUNCTION_10 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 10
FUNCTION_2 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 2
FUNCTION_3 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 3
FUNCTION_4 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 4
FUNCTION_5 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 5
FUNCTION_6 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 6
FUNCTION_7 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 7
FUNCTION_8 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 8
FUNCTION_9 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 9
FUNCTION_TAGS - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: the funtion tags
functionTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property

G

gainRatio() - Method in class weka.classifiers.trees.j48.BinC45Split

Returns (C4.5-type) gain ratio for the generated split.

gainRatio() - Method in class weka.classifiers.trees.j48.C45Split

Returns (C4.5-type) gain ratio for the generated split.

gainRatio(double[][]) - Static method in class weka.core.ContingencyTables

Computes gain ratio for contingency table (split on rows).

GainRatioAttributeEval - Class in weka.attributeSelection

GainRatioAttributeEval :

Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.

GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute).

Valid options are:

GainRatioAttributeEval() - Constructor for class weka.attributeSelection.GainRatioAttributeEval

Constructor

GainRatioSplitCrit - Class in weka.classifiers.trees.j48

Class for computing the gain ratio for a given distribution.

GainRatioSplitCrit() - Constructor for class weka.classifiers.trees.j48.GainRatioSplitCrit

gamma(double) - Static method in class weka.core.Statistics

Returns the Gamma function of the argument.

gammaTipText() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Returns the tip text for this property

GAP - Enum in weka.core.pmml.jaxbbindings

Java class for GAP.

GAUSS - Static variable in class weka.classifiers.lazy.LWL

GAUSSIAN - Static variable in class weka.datagenerators.clusterers.SubspaceCluster

cluster type: gaussian

GAUSSIAN - Static variable in class weka.filters.unsupervised.attribute.RandomProjection

distribution type: gaussian

GaussianConditionalSufficientStats - Class in weka.classifiers.trees.ht

Maintains sufficient stats for a Gaussian distribution for a numeric attribute

GaussianConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.GaussianConditionalSufficientStats

GaussianDistribution - Class in weka.core.pmml.jaxbbindings

Java class for GaussianDistribution element declaration.

GaussianDistribution() - Constructor for class weka.core.pmml.jaxbbindings.GaussianDistribution

GaussianProcesses - Class in weka.classifiers.functions

Implements Gaussian processes for regression without hyperparameter-tuning.

GaussianProcesses() - Constructor for class weka.classifiers.functions.GaussianProcesses

GE - Static variable in interface weka.core.mathematicalexpression.sym

GE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

GeneralRegression - Class in weka.classifiers.pmml.consumer

Class implementing import of PMML General Regression model.

GeneralRegression(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.GeneralRegression

Constructs a GeneralRegression classifier.

GeneralRegressionModel - Class in weka.core.pmml.jaxbbindings

Java class for GeneralRegressionModel element declaration.

GeneralRegressionModel() - Constructor for class weka.core.pmml.jaxbbindings.GeneralRegressionModel

generate() - Method in class weka.core.Javadoc

generates either the plain Javadoc (if no filename specified) or the updated file (if a filename is specified).

generate() - Method in class weka.core.ListOptions

generates the options string.

generate() - Method in class weka.core.TestInstances

Generates a new dataset

generate(String) - Method in class weka.core.TestInstances

generates a new dataset.

generateExample() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.classifiers.classification.LED24

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.classifiers.classification.RDG1

Generate an example of the dataset dataset.

generateExample() - Method in class weka.datagenerators.classifiers.regression.Expression

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Generates one example of the dataset.

generateExample() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Generate an example of the dataset.

generateExample() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Generate an example of the dataset.

generateExample() - Method in class weka.datagenerators.DataGenerator

Generates one example of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.classification.LED24

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.classification.RDG1

Generate all examples of the dataset.

generateExamples(int, Random, Instances) - Method in class weka.datagenerators.classifiers.classification.RDG1

Generate all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.regression.Expression

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Generates all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Generate all examples of the dataset.

generateExamples(Random, Instances) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Generate all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Generate all examples of the dataset.

generateExamples() - Method in class weka.datagenerators.DataGenerator

Generates all examples of the dataset.

generateFinished() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.classifiers.classification.LED24

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.classifiers.classification.RDG1

Compiles documentation about the data generation.

generateFinished() - Method in class weka.datagenerators.classifiers.regression.Expression

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Generates a comment string that documentats the data generator.

generateFinished() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Compiles documentation about the data generation after the generation process

generateFinished() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Compiles documentation about the data generation after the generation process

generateFinished() - Method in class weka.datagenerators.DataGenerator

Generates a comment string that documentates the data generator.

generateHelp() - Method in class weka.core.Javadoc

generates a string to print as help on the console

generateHelp() - Method in class weka.core.ListOptions

generates a string to print as help on the console

generateInstances() - Method in class weka.classifiers.bayes.net.BayesNetGenerator

GenerateInstances generates random instances sampling from the distribution represented by the Bayes network structure.

generateInstances(int[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Generate an instance.

generateInstances(int[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Generates a new instance using one kernel estimator.

generateInstances() - Method in class weka.gui.explorer.PreprocessPanel

sets Instances generated via DataGenerators (pops up a Dialog)

generateOutput() - Method in class weka.gui.visualize.BMPWriter

generates the actual output.

generateOutput() - Method in class weka.gui.visualize.JPEGWriter

generates the actual output.

generateOutput() - Method in class weka.gui.visualize.PNGWriter

generates the actual output.

generateOutput() - Method in class weka.gui.visualize.PostscriptWriter

generates the actual output

generatePartition(Instances) - Method in class weka.classifiers.meta.Bagging

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.meta.FilteredClassifier

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.meta.RandomCommittee

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.trees.J48

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.trees.RandomForest

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.trees.RandomTree

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in class weka.classifiers.trees.REPTree

Builds the classifier to generate a partition.

generatePartition(Instances) - Method in interface weka.core.PartitionGenerator

Builds the classifier to generate a partition.

generateRandomNetwork() - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Generate random connected Bayesian network with discrete nodes having all the same cardinality.

generateRandomNetworkStructure(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator

GenerateRandomNetworkStructure generate random connected Bayesian network

generateRankingTipText() - Method in class weka.attributeSelection.GreedyStepwise

Returns the tip text for this property

generateRankingTipText() - Method in class weka.attributeSelection.Ranker

Returns the tip text for this property

generateRules(double, ArrayList<Hashtable<ItemSet, Integer>>, int) - Method in class weka.associations.AprioriItemSet

Generates all rules for an item set.

generateRules(double, boolean) - Method in class weka.associations.LabeledItemSet

Generates rules out of item sets

generateRulesBruteForce(double, int, ArrayList<Hashtable<ItemSet, Integer>>, int, int, double) - Method in class weka.associations.AprioriItemSet

Generates all significant rules for an item set.

generateRulesBruteForce(FPGrowth.FrequentItemSets, DefaultAssociationRule.METRIC_TYPE, double, int, int, int) - Static method in class weka.associations.FPGrowth

Generate all association rules, from the supplied frequet item sets, that meet a given minimum metric threshold.

generateRulesTipText() - Method in class weka.classifiers.trees.m5.M5Base

Returns the tip text for this property

generatesOutput() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns whether regular output is generated or not.

generatesOutput() - Method in class weka.classifiers.evaluation.output.prediction.Null

Returns always false.

generateStart() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.classification.LED24

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.classification.RDG1

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.regression.Expression

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Generates a comment string that documentates the data generator.

generateStart() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Compiles documentation about the data generation before the generation process

generateStart() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Compiles documentation about the data generation before the generation process

generateStart() - Method in class weka.datagenerators.DataGenerator

Generates a comment string that documentates the data generator.

GeneratorPropertyIteratorPanel - Class in weka.gui.experiment

This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.

GeneratorPropertyIteratorPanel() - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel

Creates the property iterator panel initially disabled.

GeneratorPropertyIteratorPanel(Experiment) - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel

Creates the property iterator panel and sets the experiment.

GenericArrayEditor - Class in weka.gui

A PropertyEditor for arrays of objects that themselves have property editors.

GenericArrayEditor() - Constructor for class weka.gui.GenericArrayEditor

GenericObjectEditor - Class in weka.gui

A PropertyEditor for objects.

GenericObjectEditor() - Constructor for class weka.gui.GenericObjectEditor

Default constructor.

GenericObjectEditor(boolean) - Constructor for class weka.gui.GenericObjectEditor

Constructor that allows specifying whether it is possible to change the class within the editor dialog.

GenericObjectEditor.CapabilitiesFilterDialog - Class in weka.gui

A dialog for selecting Capabilities to look for in the GOE tree.

GenericObjectEditor.CapabilitiesFilterDialog() - Constructor for class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

creates a dialog to choose Capabilities from.

GenericObjectEditor.GOEPanel - Class in weka.gui

Handles the GUI side of editing values.

GenericObjectEditor.GOEPanel() - Constructor for class weka.gui.GenericObjectEditor.GOEPanel

Creates the GUI editor component.

GenericObjectEditor.GOETreeNode - Class in weka.gui

A specialized TreeNode for supporting filtering via Capabilities.

GenericObjectEditor.GOETreeNode() - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode

Creates a tree node that has no parent and no children, but which allows children.

GenericObjectEditor.GOETreeNode(Object) - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode

Creates a tree node with no parent, no children, but which allows children, and initializes it with the specified user object.

GenericObjectEditor.GOETreeNode(Object, boolean) - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode

Creates a tree node with no parent, no children, initialized with the specified user object, and that allows children only if specified.

GenericObjectEditor.JTreePopupMenu - Class in weka.gui

Creates a popup menu containing a tree that is aware of the screen dimensions.

GenericObjectEditor.JTreePopupMenu(JTree) - Constructor for class weka.gui.GenericObjectEditor.JTreePopupMenu

Constructs a new popup menu.

GenericObjectEditorHistory - Class in weka.gui

A helper class for maintaining a history of objects selected in the GOE.

GenericObjectEditorHistory() - Constructor for class weka.gui.GenericObjectEditorHistory

Initializes the history.

GenericObjectEditorHistory.HistorySelectionEvent - Class in weka.gui

Event that gets sent when a history item gets selected.

GenericObjectEditorHistory.HistorySelectionEvent(Object, Object) - Constructor for class weka.gui.GenericObjectEditorHistory.HistorySelectionEvent

Initializes the event.

GenericObjectEditorHistory.HistorySelectionListener - Interface in weka.gui

Interface for classes that listen to selections of history items.

GenericPropertiesCreator - Class in weka.gui

This class can generate the properties object that is normally loaded from the GenericObjectEditor.props file (= PROPERTY_FILE).

GenericPropertiesCreator() - Constructor for class weka.gui.GenericPropertiesCreator

initializes the creator, locates the props file with the Utils class.

GenericPropertiesCreator(String) - Constructor for class weka.gui.GenericPropertiesCreator

initializes the creator, the given file overrides the props-file search of the Utils class

GeneticSearch - Class in weka.classifiers.bayes.net.search.global

This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.

GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.global.GeneticSearch

GeneticSearch - Class in weka.classifiers.bayes.net.search.local

This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.

GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.local.GeneticSearch

get(int) - Method in class weka.core.Instances

Returns the instance at the given position.

get(int) - Method in class weka.core.matrix.DoubleVector

Gets a single element.

get(int) - Method in class weka.core.matrix.IntVector

Gets the value of an element.

get(int, int) - Method in class weka.core.matrix.Matrix

Get a single element.

get(int) - Method in class weka.core.PropertyPath.Path

returns the element at the given index

get(int) - Method in class weka.core.Tee

returns the specified PrintStream from the list.

get(String) - Method in class weka.core.xml.MethodHandler

returns the stored method for the given property

get(Class<?>) - Method in class weka.core.xml.MethodHandler

returns the stored method for the given class

get(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Returns the element at the specified position in this list.

get(String, String) - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the value for the specified property, if non-existent then the default value.

get(String, String) - Static method in class weka.gui.explorer.ExplorerDefaults

returns the value for the specified property, if non-existent then the default value.

getAboutPanel() - Method in class weka.gui.PropertySheetPanel

Return the panel containing global info and help for the object being edited.

getAbsoluteValue() - Method in class weka.core.pmml.jaxbbindings.Coefficients

Gets the value of the absoluteValue property.

getAccu() - Method in class weka.classifiers.rules.JRip.Antd

getAccuRate() - Method in class weka.classifiers.rules.JRip.Antd

getActionListener(JFrame) - Method in interface weka.gui.MainMenuExtension

If the extension has a custom ActionListener for the menu item, then it must be returned here.

getActivationFunction() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the activationFunction property.

getActivationFunction() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the activationFunction property.

getActualIndex(int) - Method in class weka.core.AttributeLocator

returns actual index in the Instances object.

getActualRow(int) - Method in class weka.gui.SortedTableModel

Returns the actual underlying row the given visible one represents.

getActualT1() - Method in class weka.clusterers.Canopy

Get the actual value of T1 (which may be different from the initial value if the heuristic is used)

getActualT2() - Method in class weka.clusterers.Canopy

Get the actual value of T2 (which may be different from the initial value if the heuristic is used)

getAcuity() - Method in class weka.clusterers.Cobweb

get the acuity value

getAdditional() - Method in class weka.gui.scripting.event.ScriptExecutionEvent

Returns the additional information.

getAddMatchingEndBlocks() - Method in class weka.gui.scripting.SyntaxDocument

Returns whether matching block ends are inserted or not.

getAddress() - Static method in class weka.core.Copyright

returns the address of the owner

getAdjRSquared() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the adjRSquared property.

getAdjustWeights() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns true if instance weights will be adjusted to maintain total weight per class.

getADTree() - Method in class weka.classifiers.bayes.BayesNet

get ADTree strucrture containing efficient representation of counts.

getAdvanceDataSetFirst() - Method in class weka.experiment.Experiment

Get the value of m_DataSetFirstFirst.

getAffinity() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the affinity property.

getAggregate() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the aggregate property.

getAggregate() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the aggregate property.

getAggregate() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the aggregate property.

getAIC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the aic property.

getAICc() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the aiCc property.

getAlgorithm() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the algorithm property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.MiningModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the value of the algorithmName property.

getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the algorithmName property.

getAllDependenciesForPackage(Package, Map<String, List<Dependency>>) - Static method in class weka.core.WekaPackageManager

Get a list of dependencies for a given package

getAllEvaluationMetricNames() - Static method in class weka.classifiers.evaluation.Evaluation

Utility method to get a list of the names of all built-in and plugin evaluation metrics

getAllEvaluationMetricNames() - Static method in class weka.classifiers.Evaluation

Utility method to get a list of the names of all built-in and plugin evaluation metrics

getAllMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper

Get a list of all available evaluation metric names

getAllowedIndices() - Method in class weka.core.AttributeLocator

returns the indices that are allowed to check for the attribute type

getAllowMultipleTabs() - Method in class weka.gui.beans.KnowledgeFlowApp

getAllowUnclassifiedInstances() - Method in class weka.classifiers.trees.RandomTree

Get the value of NumFolds.

getAllPackages() - Static method in class weka.core.WekaPackageManager

Get a list of all packages

getAllTheRules() - Method in class weka.associations.Apriori

returns all the rules

getAlpha() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Get prior used in probability table estimation

getAlpha() - Method in class weka.core.pmml.jaxbbindings.Level

Gets the value of the alpha property.

getAlternate() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the alternate property.

getAlternateTargetCategory() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the alternateTargetCategory property.

getAltitude() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the altitude property.

getAltitude() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the altitude property.

getAltitude() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the altitude property.

getAmplitude() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the amplitude multiplier.

getAnimatedIcon() - Method in class weka.gui.beans.BeanVisual

Returns the animated icon

getAnimatedIconPath() - Method in class weka.gui.beans.BeanVisual

returns the path for the animated icon

getAnnotation() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the annotation property.

getAnova() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the anova property.

getAnovaRow() - Method in class weka.core.pmml.jaxbbindings.Anova

Gets the value of the anovaRow property.

getAntds() - Method in class weka.classifiers.rules.JRip.RipperRule

Return the antecedents

getAntecedent() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the antecedent property.

getAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate

Gets the value of the anyDistribution property.

getAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the anyDistribution property.

getAppend() - Method in class weka.gui.beans.TextSaver

getAppendPredictedProbabilities() - Method in class weka.gui.beans.PredictionAppender

Return true if predicted probabilities are to be appended rather than class value

getApplication() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the application property.

getApplicationName() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin

Get the name to display in title bar of the enclosing JFrame for the plugin

getApply() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the apply property.

getApply() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the apply property.

getApply() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the apply property.

getArffFile() - Method in class weka.gui.streams.InstanceLoader

getArffFile() - Method in class weka.gui.streams.InstanceSavePanel

getArgs() - Method in class weka.gui.scripting.Script.ScriptThread

Returns the commandline args.

getArray() - Method in class weka.core.matrix.DoubleVector

Access the internal one-dimensional array.

getArray() - Method in class weka.core.matrix.IntVector

Access the internal one-dimensional array.

getArray() - Method in class weka.core.matrix.Matrix

Access the internal two-dimensional array.

getArray() - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.BoundaryValues

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.ClassLabels

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.CorrelationFields

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.DiscrStats

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.TextDictionary

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.TimeException

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.XCoordinates

Gets the value of the array property.

getArray() - Method in class weka.core.pmml.jaxbbindings.YCoordinates

Gets the value of the array property.

getArrayClass(Class<?>) - Static method in class weka.core.Utils

Returns the basic class of an array class (handles multi-dimensional arrays).

getArrayCopy() - Method in class weka.core.matrix.DoubleVector

Returns a copy of the DoubleVector usng a double array.

getArrayCopy() - Method in class weka.core.matrix.IntVector

Returns a copy of the internal one-dimensional array.

getArrayCopy() - Method in class weka.core.matrix.Matrix

Copy the internal two-dimensional array.

getArrayDimensions(Class<?>) - Static method in class weka.core.Utils

Returns the dimensions of the given array.

getArrayDimensions(Object) - Static method in class weka.core.Utils

Returns the dimensions of the given array.

getASCrossvalidationFolds() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default number of folds of the CV in the attribute selection panel.

getASEvaluator() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default attribute evalautor (fully configured) for the attribute selection panel.

getAsInstance(Instances, Random) - Method in class weka.core.AlgVector

Gets the elements of the vector as an instance.

getASRandomSeed() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default random seed value in the attribute selection panel.

getASSearch() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default attribute selection search scheme (fully configured) for the attribute selection panel.

getAssignments() - Method in class weka.clusterers.SimpleKMeans

Gets the assignments for each instance.

getAssociatedConnections() - Method in class weka.gui.beans.MetaBean

getAssociationModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the associationModel property.

getAssociationModelOrBaselineModelOrClusteringModels() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the associationModelOrBaselineModelOrClusteringModel property.

getAssociationRules() - Method in class weka.associations.Apriori

getAssociationRules() - Method in interface weka.associations.AssociationRulesProducer

Gets the list of mined association rules.

getAssociationRules() - Method in class weka.associations.FilteredAssociator

Gets the list of mined association rules.

getAssociationRules() - Method in class weka.associations.FPGrowth

Gets the list of mined association rules.

getAssociator() - Method in class weka.associations.CheckAssociator

Get the associator being tested

getAssociator() - Method in class weka.associations.SingleAssociatorEnhancer

Get the associator used as the base associator.

getAssociator() - Method in class weka.gui.beans.Associator

Get the associator currently set for this wrapper

getAssociator() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default associator (fully configured) for the associations panel.

getASTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default attribute selection test mode for the attribute selection panel.

getAsText() - Method in class weka.gui.beans.EnvironmentField

getAsText() - Method in class weka.gui.CostMatrixEditor

Some objects can be represented as text, but a cost matrix cannot.

getAsText() - Method in class weka.gui.GenericArrayEditor

Returns null as we don't support getting/setting values as text.

getAsText() - Method in class weka.gui.GenericObjectEditor

Returns null as we don't support getting/setting values as text.

getAsText() - Method in class weka.gui.SelectedTagEditor

Gets the current value as text.

getAsText() - Method in class weka.gui.SimpleDateFormatEditor

Returns the date format string.

getAttList_Irr() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the array that defines which of the attributes are seen to be irrelevant.

getAttr() - Method in class weka.classifiers.rules.JRip.Antd

getAttribute() - Method in class weka.associations.Item

Get the attribute that this item originates from.

getAttribute() - Method in class weka.core.pmml.jaxbbindings.Characteristic

Gets the value of the attribute property.

getAttribute1() - Method in class weka.gui.visualize.VisualizePanelEvent

getAttribute2() - Method in class weka.gui.visualize.VisualizePanelEvent

getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the attribute at the given index, can be NULL if not an attribute column

getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the attribute at the given index, can be NULL if not an attribute column

getAttributeCapabilities() - Method in class weka.core.Capabilities

returns all attribute capabilities

getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the column of the given attribute name, -1 if not found

getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffTableModel

returns the column of the given attribute name, -1 if not found

getAttributeID() - Method in class weka.experiment.ClassifierSplitEvaluator

Get the index of Attibute Identifying the instances

getAttributeIndex() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns the index of the attribute used in the regression.

getAttributeIndex() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression

Returns the index of the attribute used in the regression.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.Add

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.AddNoise

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.AddValues

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Gets the index of the attribute converted.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Get the index of the attribute used.

getAttributeIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Get the index of the attribute used.

getAttributeIndexes() - Method in class weka.filters.unsupervised.attribute.NominalToString

Get the index of the attribute used.

getAttributeIndices() - Method in class weka.core.AttributeLocator

Returns the indices of the attributes.

getAttributeIndices() - Method in interface weka.core.DistanceFunction

Gets the range of attributes used in the calculation of the distance.

getAttributeIndices() - Method in class weka.core.NormalizableDistance

Gets the range of attributes used in the calculation of the distance.

getAttributeIndices() - Method in class weka.filters.supervised.attribute.Discretize

Gets the current range selection

getAttributeIndices() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Get the current range selection.

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Get the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Copy

Get the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Get the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Get the current range selection.

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Gets the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Gets the selection of the columns, e.g., first-last or first-3,5-last

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Gets the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Get the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Remove

Get the current range selection.

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Gets the current range selection.

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Reorder

Get the current range selection

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.SortLabels

Gets the current selected attributes.

getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets the current range selection.

getAttributeName() - Method in class weka.filters.unsupervised.attribute.Add

Get the name of the attribute to be created.

getAttributeName() - Method in class weka.filters.unsupervised.attribute.AddID

Get the name of the attribute to be created

getAttributeNamePrefix() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Get the attribute name prefix.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Get the range of indices of the attributes used.

getAttributes() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the range of attributes to output.

getAttributes() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getAttributes() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Get the list of attributes to consider for replacing missing values

getAttributes() - Method in class weka.gui.arffviewer.ArffPanel

returns a list with the attributes

getAttributeSelectionMethod() - Method in class weka.classifiers.functions.LinearRegression

Gets the method used to select attributes for use in the linear regression.

getAttributeSpecs() - Method in class weka.filters.unsupervised.attribute.AddUserFields

Get the list of attribute specs to use to create the new attributes.

getAttributeType() - Method in class weka.filters.unsupervised.attribute.Add

Gets the type of attribute to generate.

getAttributeType() - Method in class weka.filters.unsupervised.attribute.RemoveType

Gets the attribute type to be deleted by the filter.

getAttributeTypes() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Returns the current attribute - attribute-type relation in use.

getAttrIndexRange() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

returns the attribute range(s).

getAttrValue() - Method in class weka.classifiers.rules.JRip.Antd

getAttsToApplyTo() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Get the attributes to apply the rule to

getAttsToApplyTo() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Get the attributes to apply the rule to

getAutoBuild() - Method in class weka.classifiers.functions.MultilayerPerceptron

getAutoKeyGeneration() - Method in class weka.core.converters.DatabaseSaver

Gets whether or not a primary key will be generated automatically.

getAvailableCompatiblePackages() - Static method in class weka.core.WekaPackageManager

Get a list of the most recent version of all available packages (i.e.

getAvailablePackages() - Static method in class weka.core.WekaPackageManager

Get a list of all available packages (i.e.

getAverage(int) - Method in class weka.experiment.ResultMatrix

returns the average of the mean at the given position, if the position is valid, otherwise 0.

getAverageInstancesPerSecond() - Method in class weka.gui.beans.StreamThroughput

Get the average instances per second

getAvgNumberOfItemsPerTA() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the avgNumberOfItemsPerTA property.

getAvgNumberOfItemsPerTransaction() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the avgNumberOfItemsPerTransaction property.

getAvgNumberOfTAsPerTAGroup() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the avgNumberOfTAsPerTAGroup property.

getBackground() - Method in class weka.gui.visualize.BMPWriter

returns the current background color.

getBackground() - Method in class weka.gui.visualize.JPEGWriter

returns the current background color.

getBackground() - Method in class weka.gui.visualize.PNGWriter

returns the current background color.

getBackground() - Method in class weka.gui.visualize.PostscriptGraphics

getBackgroundColor() - Method in class weka.gui.scripting.SyntaxDocument

Returns the background color.

getBackup() - Method in class weka.gui.GenericObjectEditor

Returns the backup object (may be null if there is no backup.

getBagSizePercent() - Method in class weka.classifiers.meta.Bagging

Gets the size of each bag, as a percentage of the training set size.

getBalanceClass() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Gets whether the class is balanced.

getBallSplitter() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Returns the BallSplitter algorithm set that would be used by the TopDown BallTree constructor.

getBallTreeConstructor() - Method in class weka.core.neighboursearch.BallTree

Returns the BallTreeConstructor currently in use.

getBase() - Method in class weka.core.neighboursearch.CoverTree

Returns the base in use for expansion constant.

getBaseExperiment() - Method in class weka.experiment.RemoteExperiment

Get the base experiment used by this remote experiment

getBaseline() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the baseline property.

getBaselineCell() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables

Gets the value of the baselineCell property.

getBaselineCell() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Gets the value of the baselineCell property.

getBaselineMethod() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the baselineMethod property.

getBaselineModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the baselineModel property.

getBaselineScore() - Method in class weka.core.pmml.jaxbbindings.Characteristic

Gets the value of the baselineScore property.

getBaselineScore() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the baselineScore property.

getBaselineStrataVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the baselineStrataVariable property.

getBaselineStratum() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables

Gets the value of the baselineStratum property.

getBatchSize() - Method in interface weka.core.BatchPredictor

Get the batch size to use.

getBayesInput() - Method in class weka.core.pmml.jaxbbindings.BayesInputs

Gets the value of the bayesInput property.

getBean() - Method in class weka.gui.beans.BeanInstance

Gets the bean encapsulated in this instance

getBeanContext() - Method in class weka.gui.beans.AbstractDataSource

Return the bean context (if any) that this bean is embedded in

getBeanContext() - Method in class weka.gui.beans.CostBenefitAnalysis

getBeanContext() - Method in class weka.gui.beans.DataVisualizer

Return the bean context (if any) that this bean is embedded in

getBeanContext() - Method in class weka.gui.beans.GraphViewer

Return the bean context (if any) that this bean is embedded in

getBeanContext() - Method in class weka.gui.beans.ModelPerformanceChart

Return the bean context (if any) that this bean is embedded in

getBeanContext() - Method in class weka.gui.beans.TextViewer

Return the bean context (if any) that this bean is embedded in

getBeanDescriptor() - Method in class weka.filters.unsupervised.attribute.AddUserFieldsBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.AssociatorBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.AttributeSummarizerBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.ClassAssignerBeanInfo

getBeanDescriptor() - Method in class weka.gui.beans.ClassifierBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.ClassValuePickerBeanInfo

getBeanDescriptor() - Method in class weka.gui.beans.ClustererBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo

Return the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.DataVisualizerBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.FilterBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.FlowByExpressionBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.ImageSaverBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo

Return the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.JoinBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.LoaderBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.ModelPerformanceChartBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.NoteBeanInfo

getBeanDescriptor() - Method in class weka.gui.beans.PredictionAppenderBeanInfo

Return the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.SaverBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.SerializedModelSaverBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.SorterBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.StripChartBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.SubstringLabelerBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.SubstringReplacerBeanInfo

Get the bean descriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.TextSaverBeanInfo

Get BeanDescriptor for this bean

getBeanDescriptor() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo

Get the bean descriptor for this bean

getBeanInfoInputs() - Method in class weka.gui.beans.MetaBean

getBeanInfoOutputs() - Method in class weka.gui.beans.MetaBean

getBeanInfoSubFlow() - Method in class weka.gui.beans.MetaBean

getBeanInstances(Integer...) - Static method in class weka.gui.beans.BeanInstance

Return the list of displayed beans

getBeanLayout(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getBeansInInputs() - Method in class weka.gui.beans.MetaBean

Return all the beans in the inputs

getBeansInOutputs() - Method in class weka.gui.beans.MetaBean

Return all the beans in the outputs

getBeansInSubFlow() - Method in class weka.gui.beans.MetaBean

Return all the beans in the sub flow

getBestClassifierIndex() - Method in class weka.classifiers.meta.MultiScheme

Get the index of the classifier that was determined as best during cross-validation.

getBestClassifierOptions() - Method in class weka.classifiers.meta.CVParameterSelection

Returns (a copy of) the best options found for the classifier.

getBestFit() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the value of the bestFit property.

getBeta() - Method in class weka.core.pmml.jaxbbindings.PCell

Gets the value of the beta property.

getBias() - Method in class weka.classifiers.BVDecompose

Get the calculated bias squared

getBias() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the bias property.

getBiasToUniformClass() - Method in class weka.filters.supervised.instance.Resample

Gets the bias towards a uniform class.

getBIC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the bic property.

getBIFFile() - Method in class weka.classifiers.bayes.BayesNet

Get name of network in BIF file to compare with

getBIFFile() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Get name of network in BIF file to read structure from

getBIFHeader() - Method in class weka.classifiers.bayes.BayesNet

getBinarizeNumericAttributes() - Method in class weka.attributeSelection.InfoGainAttributeEval

get whether numeric attributes are just being binarized.

getBinaryAttributesNominal() - Method in class weka.filters.supervised.attribute.NominalToBinary

Gets if binary attributes are to be treated as nominal ones.

getBinaryAttributesNominal() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Gets if binary attributes are to be treated as nominal ones.

getBinarySimilarity() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the binarySimilarity property.

getBinarySplits() - Method in class weka.classifiers.rules.PART

Get the value of binarySplits.

getBinarySplits() - Method in class weka.classifiers.trees.J48

Get the value of binarySplits.

getBinRangePrecision() - Method in class weka.filters.supervised.attribute.Discretize

Get the precision for bin boundaries.

getBinRangesString(int) - Method in class weka.filters.supervised.attribute.Discretize

Gets the bin ranges string for an attribute

getBinRangesString(int) - Method in class weka.filters.unsupervised.attribute.Discretize

Gets the bin ranges string for an attribute

getBins() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets the number of bins numeric attributes will be divided into

getBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Ignored

getBinValue() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin

Gets the value of the binValue property.

getBlockEnd() - Method in class weka.gui.scripting.SyntaxDocument

Returns the end of a block.

getBlockOnLastFold() - Method in class weka.gui.beans.Classifier

Gets whether we are blocking on the last fold of the last run rather than rejecting any further data until all processing has been completed.

getBlockStart() - Method in class weka.gui.scripting.SyntaxDocument

Returns the start of a block.

getBooleanCols() - Method in class weka.datagenerators.ClusterGenerator

returns the range of boolean attributes.

getBooleanOperator() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate

Gets the value of the booleanOperator property.

getBooleanOperator() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Gets the value of the booleanOperator property.

getBorderInsets(Component) - Method in class weka.gui.beans.ShadowBorder

Returns a new Insets instance where the top and left are 1, the bottom and right fields are the border width + 1.

getBorderInsets(Component, Insets) - Method in class weka.gui.beans.ShadowBorder

Reinitializes the insets parameter with this ShadowBorder's current Insets.

getBoundaryValueMeans() - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Gets the value of the boundaryValueMeans property.

getBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Gets the value of the boundaryValues property.

getBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Gets the value of the boundaryValues property.

getBuffer() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the current buffer.

getBufferSize() - Method in class weka.core.converters.CSVLoader

Get the buffer size to use - i.e.

getBufferSize() - Method in class weka.gui.beans.Sorter

Get the size of the in-memory buffer

getBuilder() - Method in class weka.core.xml.XMLDocument

returns the DocumentBuilder.

getBuildLogisticModels() - Method in class weka.classifiers.functions.SMO

Get the value of buildLogisticModels.

getBuildRegressionTree() - Method in class weka.classifiers.trees.m5.M5Base

Get the value of regressionTree.

getBuiltInMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper

Get a list of built-in metric names

getBusinessProblem() - Method in class weka.core.pmml.jaxbbindings.Decisions

Gets the value of the businessProblem property.

getC() - Method in class weka.classifiers.functions.SMO

Get the value of C.

getC() - Method in class weka.classifiers.functions.SMOreg

Get the value of C.

getC00Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the c00Parameter property.

getC01Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the c01Parameter property.

getC10Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the c10Parameter property.

getC11Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the c11Parameter property.

getCacheHits() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

return the number of kernel cache hits

getCacheKeyName() - Method in class weka.experiment.DatabaseResultListener

Get the value of CacheKeyName.

getCacheSize() - Method in class weka.classifiers.functions.supportVector.CachedKernel

Gets the size of the cache

getCacheSize() - Method in class weka.classifiers.functions.supportVector.StringKernel

Gets the size of the cache

getCacheValues(double) - Method in class weka.classifiers.lazy.kstar.KStarCache

Returns the values in the cache mapped by the specified key

getCalcOutOfBag() - Method in class weka.classifiers.meta.Bagging

Get whether the out of bag error is calculated.

getCalculatedNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise

Gets the calculated number of attributes to retain.

getCalculatedNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch

Gets the calculated number of attributes to retain.

getCalculatedNumToSelect() - Method in class weka.attributeSelection.Ranker

Gets the calculated number to select.

getCalculateStdDevs() - Method in class weka.experiment.AveragingResultProducer

Get the value of CalculateStdDevs.

getCanChangeClassInDialog() - Method in class weka.gui.GenericObjectEditor

Returns whether the user can change the class in the dialog.

getCanopies() - Method in class weka.clusterers.Canopy

Get the canopies (cluster centers).

getCanopyMaxNumCanopiesToHoldInMemory() - Method in class weka.clusterers.SimpleKMeans

Get the maximum number of candidate canopies to retain in memory during training.

getCanopyMinimumCanopyDensity() - Method in class weka.clusterers.SimpleKMeans

Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.

getCanopyPeriodicPruningRate() - Method in class weka.clusterers.SimpleKMeans

Get the how often to prune low density canopies during training (if using canopy clustering)

getCanopyT1() - Method in class weka.clusterers.SimpleKMeans

Get the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

getCanopyT2() - Method in class weka.clusterers.SimpleKMeans

Get the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

getCapabilities() - Method in class weka.associations.AbstractAssociator

Returns the Capabilities of this associator.

getCapabilities() - Method in class weka.associations.Apriori

Returns default capabilities of the classifier.

getCapabilities() - Method in interface weka.associations.Associator

Returns the Capabilities of this associator.

getCapabilities() - Method in class weka.associations.FilteredAssociator

Returns default capabilities of the associator.

getCapabilities() - Method in class weka.associations.FPGrowth

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.associations.SingleAssociatorEnhancer

Returns default capabilities of the base associator.

getCapabilities() - Method in class weka.attributeSelection.ASEvaluation

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.CfsSubsetEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.CorrelationAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.GainRatioAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.OneRAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.PrincipalComponents

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.classifiers.AbstractClassifier

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.bayes.BayesNet

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayes

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns default capabilities of the classifier.

getCapabilities() - Method in interface weka.classifiers.Classifier

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.GaussianProcesses

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.LinearRegression

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.Logistic

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.MultilayerPerceptron

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SGD

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SGDText

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SimpleLogistic

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SMO

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.SMOreg

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.Puk

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the Capabilities of this kernel.

getCapabilities() - Method in class weka.classifiers.functions.VotedPerceptron

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.lazy.IBk

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.lazy.KStar

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.lazy.LWL

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AdaBoostM1

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AdditiveRegression

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.ClassificationViaRegression

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.CVParameterSelection

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.FilteredClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.LogitBoost

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.MultiClassClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.Stacking

Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.

getCapabilities() - Method in class weka.classifiers.meta.Vote

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.misc.SerializedClassifier

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.MultipleClassifiersCombiner

Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.

getCapabilities() - Method in class weka.classifiers.rules.DecisionTable

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.rules.JRip

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.rules.OneR

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.rules.PART

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.rules.part.MakeDecList

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.rules.ZeroR

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.SingleClassifierEnhancer

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.trees.DecisionStump

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.HoeffdingTree

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree

Returns default capabilities of the classifier tree.

getCapabilities() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns default capabilities of the classifier tree.

getCapabilities() - Method in class weka.classifiers.trees.J48

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree

Returns default capabilities of the classifier tree.

getCapabilities() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree

Returns default capabilities of the classifier tree.

getCapabilities() - Method in class weka.classifiers.trees.LMT

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.m5.M5Base

Returns default capabilities of the classifier, i.e., of LinearRegression.

getCapabilities() - Method in class weka.classifiers.trees.RandomForest

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.RandomTree

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.REPTree

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.clusterers.AbstractClusterer

Returns the Capabilities of this clusterer.

getCapabilities() - Method in class weka.clusterers.Canopy

Returns default capabilities of the clusterer.

getCapabilities() - Method in interface weka.clusterers.Clusterer

Returns the Capabilities of this clusterer.

getCapabilities() - Method in class weka.clusterers.Cobweb

Returns default capabilities of the clusterer.

getCapabilities() - Method in class weka.clusterers.EM

Returns default capabilities of the clusterer (i.e., the ones of SimpleKMeans).

getCapabilities() - Method in class weka.clusterers.FarthestFirst

Returns default capabilities of the clusterer.

getCapabilities() - Method in class weka.clusterers.FilteredClusterer

Returns default capabilities of the clusterer.

getCapabilities() - Method in class weka.clusterers.HierarchicalClusterer

getCapabilities() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns default capabilities of the clusterer (i.e., of the wrapper clusterer).

getCapabilities() - Method in class weka.clusterers.SimpleKMeans

Returns default capabilities of the clusterer.

getCapabilities() - Method in class weka.clusterers.SingleClustererEnhancer

Returns default capabilities of the clusterer.

getCapabilities() - Method in interface weka.core.CapabilitiesHandler

Returns the capabilities of this object.

getCapabilities() - Method in class weka.core.converters.AbstractSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.ArffSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.C45Saver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.CSVSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.DatabaseSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.JSONSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.LibSVMSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.MatlabSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.SerializedInstancesSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.SVMLightSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.XRFFSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.FindWithCapabilities

The capabilities to search for.

getCapabilities() - Method in class weka.estimators.DiscreteEstimator

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.estimators.Estimator

Returns the Capabilities of this Estimator.

getCapabilities() - Method in class weka.estimators.KernelEstimator

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.estimators.MahalanobisEstimator

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.estimators.NormalEstimator

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.estimators.PoissonEstimator

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.filters.AllFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.Filter

Returns the Capabilities of this filter.

getCapabilities(Instances) - Method in class weka.filters.Filter

Returns the Capabilities of this filter, customized based on the data.

getCapabilities() - Method in class weka.filters.MultiFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.SimpleFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.AttributeSelection

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.ClassOrder

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.Discretize

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.NominalToBinary

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.PartitionMembership

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.instance.Resample

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Add

Returns the Capabilities of this filter.

getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddID

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddUserFields

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Center

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns the Capabilities of this filter.

getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Copy

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Discretize

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToString

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericToBinary

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Obfuscate

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Remove

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Reorder

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Standardize

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SwapValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Transpose

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.Randomize

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.Resample

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

returns the currently selected capabilities.

getCapabilitiesFilter() - Method in class weka.gui.ConverterFileChooser

returns the capabilities filter for the savers, can be null if all are listed.

getCapabilitiesFilter() - Method in class weka.gui.GenericObjectEditor

Returns the current Capabilities filter, can be null.

getCar() - Method in class weka.associations.Apriori

Gets whether class association ruels are mined

getCardinality(int) - Method in class weka.classifiers.bayes.BayesNet

get number of values a node can take

getCardinality() - Method in class weka.core.pmml.jaxbbindings.Counts

Gets the value of the cardinality property.

getCardinality() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Gets the cardinality of the attributes (incl class attribute)

getCardinalityOfParents() - Method in class weka.classifiers.bayes.net.ParentSet

returns cardinality of parents

getCaseSensitive() - Method in class weka.gui.scripting.SyntaxDocument

Returns whether blanks are used instead of tabs.

getCastInteger() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the castInteger property.

getCategoricalPredictor() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the categoricalPredictor property.

getCategoricalScoringMethod() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the categoricalScoringMethod property.

getCategories() - Method in class weka.core.pmml.jaxbbindings.Predictor

Gets the value of the categories property.

getCategory() - Method in class weka.core.pmml.jaxbbindings.Categories

Gets the value of the category property.

getCategory() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the category property.

getCell(int, int) - Method in class weka.classifiers.CostMatrix

Return the contents of a particular cell.

getCellEditor(int, int) - Method in class weka.gui.arffviewer.ArffTable

returns the cell editor for the given cell

getCells() - Method in class weka.gui.sql.ResultSetHelper

returns an 2-dimensional array with the content of the resultset, the first dimension is the row, the second the column (i.e., getCells()[y][x]).

getCenter() - Method in class weka.gui.treevisualizer.Node

Get the value of center.

getCenterData() - Method in class weka.attributeSelection.PrincipalComponents

Get whether to center (rather than standardize) the data.

getCenterData() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Get whether to center (rather than standardize) the data.

getChangeInWeights() - Method in class weka.classifiers.functions.neural.NeuralNode

call this function to get the chnage in weights array.

getChar() - Method in class weka.core.Trie.TrieNode

returns the stored character

getCharacteristic() - Method in class weka.core.pmml.jaxbbindings.Characteristics

Gets the value of the characteristic property.

getCharSet() - Method in class weka.core.converters.TextDirectoryLoader

Get the character set to use when reading text files.

getChartingEvalWindowSize() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Get whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).

getChebychev() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the chebychev property.

getChecked(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

returns the checked state of the element at the given index

getChecked(int) - Method in class weka.gui.CheckBoxList

returns the checked state of the element at the given index

getCheckedIndices() - Method in class weka.gui.CheckBoxList

returns an array with the indices of all checked items

getCheckErrorRate() - Method in class weka.classifiers.rules.JRip

Gets whether to check for error rate is in stopping criterion

getChecksTurnedOff() - Method in class weka.classifiers.functions.SMO

Returns whether the checks are turned off or not.

getChecksTurnedOff() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns whether the checks are turned off or not.

getChecksTurnedOff() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns whether the checks are turned off or not.

getChild(String) - Method in class weka.core.json.JSONNode

Returns the child with the given name.

getChild(int) - Method in class weka.gui.treevisualizer.Node

Get the Edge for the child number 'i'.

getChildField() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the childField property.

getChildParent() - Method in class weka.core.pmml.jaxbbindings.Taxonomy

Gets the value of the childParent property.

getChildren(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

return list of children of a node

getChildTags(Node) - Static method in class weka.core.xml.XMLDocument

returns all non tag-children from the given node.

getChildTags(Node, String) - Static method in class weka.core.xml.XMLDocument

returns all non tag-children from the given node.

getChiSquareValue() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the chiSquareValue property.

getChooseClassPopupMenu() - Method in class weka.gui.GenericObjectEditor

Returns a popup menu that allows the user to change the class of object.

getCindex() - Method in class weka.gui.visualize.PlotData2D

Get the currently set colouring index of the data

getCIndex() - Method in class weka.gui.visualize.VisualizePanel

Get the index of the attribute selected for coloring

getCityBlock() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the cityBlock property.

getClassAttribute() - Method in class weka.gui.beans.ThresholdDataEvent

Return the class attribute for which the threshold data was generated for.

getClassCapabilities() - Method in class weka.core.Capabilities

returns all class capabilities

getClassColumn() - Method in class weka.gui.beans.ClassAssigner

getClassCounts() - Method in class weka.filters.supervised.attribute.ClassOrder

Get the class distribution of the sorted class values.

getClassesToClusters() - Method in class weka.clusterers.ClusterEvaluation

Return the array (ordered by cluster number) of minimum error class to cluster mappings

getClassFlag() - Method in class weka.datagenerators.ClusterGenerator

Gets the class flag.

getClassForIRStatistics() - Method in class weka.experiment.ClassifierSplitEvaluator

Get the value of ClassForIRStatistics.

getClassificationMethod() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the classificationMethod property.

getClassifier() - Method in class weka.attributeSelection.WrapperSubsetEval

Get the classifier used as the base learner.

getClassifier() - Method in class weka.classifiers.BVDecompose

Gets the name of the classifier being analysed

getClassifier() - Method in class weka.classifiers.BVDecomposeSegCVSub

Gets the name of the classifier being analysed

getClassifier() - Method in class weka.classifiers.CheckClassifier

Get the classifier used as the classifier

getClassifier() - Method in class weka.classifiers.CheckSource

Gets the classifier being used for the tests, can be null.

getClassifier(int) - Method in class weka.classifiers.meta.MultiScheme

Gets a single classifier from the set of available classifiers.

getClassifier(int) - Method in class weka.classifiers.MultipleClassifiersCombiner

Gets a single classifier from the set of available classifiers.

getClassifier() - Method in class weka.classifiers.SingleClassifierEnhancer

Get the classifier used as the base learner.

getClassifier() - Method in class weka.experiment.ClassifierSplitEvaluator

Get the value of Classifier.

getClassifier() - Method in class weka.experiment.RegressionSplitEvaluator

Get the value of Classifier.

getClassifier() - Method in class weka.filters.supervised.attribute.AddClassification

Gets the classifier used by the filter.

getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the classifier used by the filter.

getClassifier() - Method in class weka.gui.beans.BatchClassifierEvent

Get the classifier

getClassifier() - Method in class weka.gui.beans.Classifier

Get the currently trained classifier.

getClassifier() - Method in class weka.gui.beans.IncrementalClassifierEvent

Get the classifier

getClassifier() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Returns the currently set classifier.

getClassifier() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default classifier (fully configured) for the classify panel.

getClassifierCostSensitiveEval() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the evaluation of the classifier is done cost-sensitively.

getClassifierCrossvalidationFolds() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default number of folds of the CV in the classify panel.

getClassifierErrorsMaximumPlotSizeNumeric() - Static method in class weka.gui.explorer.ExplorerDefaults

Returns the maximum size in pixels for plots of plotting classifier errors of numeric attributes.

getClassifierErrorsMinimumPlotSizeNumeric() - Static method in class weka.gui.explorer.ExplorerDefaults

Returns the minimum size in pixels for plots of plotting classifier errors of numeric attributes.

getClassifierErrorsPlotInstances() - Static method in class weka.gui.explorer.ExplorerDefaults

Returns an instance of the class used for generating plot instances for displaying the classifier errors.

getClassifierOutputAdditionalAttributes() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the string with the additional indices to output alongside the predictions.

getClassifierOutputConfusionMatrix() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the confusion matrix for the classifier is output.

getClassifierOutputEntropyEvalMeasures() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether entropy-based evaluation meastures of the classifier are output.

getClassifierOutputModel() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the built model is output.

getClassifierOutputPerClassStats() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether additional per-class stats of the classifier are output.

getClassifierOutputPredictions() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the predictions of the classifier are output as well.

getClassifierOutputSourceCode() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the source of a sourcable Classifier is output in the classify tab.

getClassifierPercentageSplit() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default classifier test mode for the classify panel (0-99).

getClassifierPreserveOrder() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the order is preserved in case of the percentage split in the classify tab.

getClassifierRandomSeed() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default random seed value for the classifier for the classify panel.

getClassifiers() - Method in class weka.classifiers.meta.MultiScheme

Gets the list of possible classifers to choose from.

getClassifiers() - Method in class weka.classifiers.MultipleClassifiersCombiner

Gets the list of possible classifers to choose from.

getClassifierSourceCodeClass() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default classname for a sourcable Classifier in the classify tab.

getClassifierStorePredictionsForVis() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the predictions of the classifier are stored for visualization.

getClassifierTemplate() - Method in class weka.gui.beans.Classifier

Return the classifier template currently in use.

getClassifierTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default classifier test mode for the classify panel.

getClassifyIterations() - Method in class weka.classifiers.BVDecomposeSegCVSub

Gets the number of times an instance is classified

getClassIndex() - Method in class weka.associations.Apriori

Gets the class index

getClassIndex() - Method in class weka.associations.FilteredAssociator

Gets the class index

getClassIndex() - Method in class weka.classifiers.BVDecompose

Get the index (starting from 1) of the attribute used as the class.

getClassIndex() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the index (starting from 1) of the attribute used as the class.

getClassIndex() - Method in class weka.classifiers.CheckSource

Gets the class index of the dataset.

getClassIndex() - Method in class weka.core.converters.JSONSaver

Get the index of the class attribute.

getClassIndex() - Method in class weka.core.converters.LibSVMSaver

Get the index of the class attribute.

getClassIndex() - Method in class weka.core.converters.SVMLightSaver

Get the index of the class attribute.

getClassIndex() - Method in class weka.core.converters.XRFFSaver

Get the index of the class attribute.

getClassIndex() - Method in class weka.core.FindWithCapabilities

returns the current current class index, -1 if no class attribute.

getClassIndex() - Method in class weka.core.TestInstances

returns the current class index (0-based), -1 is last attribute

getClassIndex() - Method in class weka.filters.CheckSource

Gets the class index of the dataset.

getClassIndex() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

returns the class index.

getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the attribute on which misclassifications are based.

getClassIndex() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Returns the 0-based class index.

getClassIndex() - Method in class weka.gui.SetInstancesPanel

Returns the currently selected class index.

getClassLabels() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix

Gets the value of the classLabels property.

getClassLoader() - Method in class weka.core.scripting.Groovy

returns the currently used Groovy classloader.

getClassMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns all the class/package matches with the partial search string.

getClassname() - Method in class weka.core.Javadoc

returns the current classname

getClassname() - Method in class weka.core.ListOptions

returns the current classname

getClassName() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Get the class containing the transformation method.

getClassname(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns the classname part of the partial classname.

getClassnames(String) - Method in class weka.core.ClassCache

Returns all the classes for the given package.

getClassnames(String) - Static method in class weka.gui.GenericObjectEditor

Returns the available classnames for a certain property in the props file.

getClassOrder() - Method in class weka.filters.supervised.attribute.ClassOrder

Get the wanted class order

getClassPriors() - Method in class weka.classifiers.evaluation.Evaluation

Get the current weighted class counts.

getClassPriors() - Method in class weka.classifiers.Evaluation

Get the current weighted class counts.

getClassType() - Method in class weka.core.TestInstances

returns the current class type

getClassValue() - Method in class weka.gui.beans.ClassValuePicker

Gets the class value considered to be the "positive" class value.

getClassValueIndex() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Get the class value index to use

getClassWeightedAverageStatistic(String) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric

Get the weighted (by class) average for this statistic.

getClearEachDataset() - Method in class weka.gui.streams.InstanceViewer

getClip() - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

getClipBounds() - Method in class weka.gui.visualize.PostscriptGraphics

This returns the full current drawing area

getClipBounds(Rectangle) - Method in class weka.gui.visualize.PostscriptGraphics

This returns the full current drawing area

getClipRect() - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

getClock() - Method in class weka.core.Debug

returns the instance of the Clock that is internally used

getClosestConnections(Point, int, Integer...) - Static method in class weka.gui.beans.BeanConnection

Return a list of connections within some delta of a point

getClosestConnectorPoint(Point) - Method in class weka.gui.beans.BeanVisual

Returns the coordinates of the closest "connector" point to the supplied point.

getCloseTo() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the "close to" number.

getCloseToDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the "close to" default.

getCloseToTolerance() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the "close to" Tolerance.

getClosure() - Method in class weka.core.pmml.jaxbbindings.Interval

Gets the value of the closure property.

getClusterAssignments() - Method in class weka.clusterers.ClusterEvaluation

Return an array of cluster assignments corresponding to the most recent set of instances clustered.

getClusterCanopyAssignments() - Method in class weka.clusterers.Canopy

Get the canopies that each canopy (cluster center) is within T1 distance of

getClusterCentroids() - Method in class weka.clusterers.FarthestFirst

Get the centroids found by FarthestFirst

getClusterCentroids() - Method in class weka.clusterers.SimpleKMeans

Gets the the cluster centroids.

getClusterDefinitions() - Method in class weka.datagenerators.clusterers.SubspaceCluster

returns the currently set clusters

getClusterer() - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator

Get the clusterer

getClusterer() - Method in class weka.clusterers.CheckClusterer

Get the clusterer used as the clusterer

getClusterer() - Method in class weka.clusterers.MakeDensityBasedClusterer

Gets the clusterer being wrapped.

getClusterer() - Method in class weka.clusterers.SingleClustererEnhancer

Get the clusterer used as the base clusterer.

getClusterer() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Get the value of clusterer

getClusterer() - Method in class weka.filters.unsupervised.attribute.AddCluster

Gets the clusterer used by the filter.

getClusterer() - Method in class weka.gui.beans.BatchClustererEvent

Get the clusterer

getClusterer() - Method in class weka.gui.beans.Clusterer

Get the clusterer currently set for this wrapper

getClusterer() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances

Returns the currently set clusterer.

getClusterer() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default clusterer (fully configured) for the clusterer panel.

getClustererAssignmentsPlotInstances() - Static method in class weka.gui.explorer.ExplorerDefaults

Returns an instance of the class used for generating plot instances for displaying the cluster assignments.

getClustererStoreClustersForVis() - Static method in class weka.gui.explorer.ExplorerDefaults

returns whether the clusters are storeed for visualization purposes in the cluster panel.

getClustererTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default cluster test mode for the cluster panel.

getClusterEvaluation() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances

Returns the cluster evaluation object in use.

getClusteringModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the clusteringModel property.

getClusteringModelQuality() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation

Gets the value of the clusteringModelQuality property.

getClusterModelsNumericAtts() - Method in class weka.clusterers.EM

Return the normal distributions for the cluster models

getClusterNominalCounts() - Method in class weka.clusterers.SimpleKMeans

Returns for each cluster the frequency counts for the values of each nominal attribute.

getClusterPriors() - Method in class weka.clusterers.EM

Return the priors for the clusters

getClusterSizes() - Method in class weka.clusterers.SimpleKMeans

Gets the number of instances in each cluster.

getClusterStandardDevs() - Method in class weka.clusterers.SimpleKMeans

Gets the standard deviations of the numeric attributes in each cluster.

getClusterSubType() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Gets the cluster sub type.

getClusterType() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Gets the cluster type.

getCoef0() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Gets the value of the coef0 property.

getCoef0() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Gets the value of the coef0 property.

getCoefficient() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Gets the value of the coefficient property.

getCoefficient() - Method in class weka.core.pmml.jaxbbindings.Coefficients

Gets the value of the coefficient property.

getCoefficient() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Gets the value of the coefficient property.

getCoefficient() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Gets the value of the coefficient property.

getCoefficients() - Method in class weka.core.matrix.LinearRegression

returns the calculated coefficients

getCoefficients() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the coefficients property.

getCol() - Method in class weka.core.pmml.jaxbbindings.MatCell

Gets the value of the col property.

getColCount() - Method in class weka.experiment.ResultMatrix

returns the number of columns.

getColHidden(int) - Method in class weka.experiment.ResultMatrix

returns the hidden status of the column, if the index is valid, otherwise false.

getCollapseTree() - Method in class weka.classifiers.trees.J48

Get the value of collapseTree.

getColName(int) - Method in class weka.experiment.ResultMatrix

returns the name of the row, if the index is valid, otherwise null.

getColNameWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the column names.

getColor() - Method in class weka.gui.ReaderToTextPane

Returns the color in use.

getColor() - Method in class weka.gui.treevisualizer.Node

Get the value of color.

getColor() - Method in class weka.gui.visualize.PostscriptGraphics

Get current pen color.

getColorBox() - Method in class weka.gui.AttributeVisualizationPanel

Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.

getColOrder() - Method in class weka.experiment.ResultMatrix

returns the current order of the columns, null means the default order.

getColoringIndex() - Method in class weka.gui.AttributeVisualizationPanel

Get the coloring (class) index for the plot

getColoringIndex() - Method in class weka.gui.beans.AttributeSummarizer

Return the coloring index for the attribute summary plots

getColors() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Get the current vector of Color objects used for the classes

getColumn(int) - Method in class weka.core.Matrix

Deprecated. Gets a column of the matrix and returns it as a double array.

getColumn() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair

Gets the value of the column property.

getColumn() - Method in class weka.core.pmml.jaxbbindings.InstanceField

Gets the value of the column property.

getColumn() - Method in class weka.core.pmml.jaxbbindings.VerificationField

Gets the value of the column property.

getColumn() - Static method in class weka.gui.experiment.ExperimenterDefaults

the comma-separated list of attribute names that identify a column.

getColumnClass(int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the most specific superclass for all the cell values in the column (always String)

getColumnClass(int) - Method in class weka.gui.beans.InteractiveTableModel

getColumnClass(int) - Method in class weka.gui.SortedTableModel

Returns the most specific superclass for all the cell values in the column.

getColumnClass(int) - Method in class weka.gui.sql.ResultSetTableModel

returns the most specific superclass for all the cell values in the column (always String).

getColumnClasses() - Method in class weka.gui.sql.ResultSetHelper

returns the classes for the columns.

getColumnCount() - Method in class weka.gui.arffviewer.ArffTableModel

returns the number of columns in the model

getColumnCount() - Method in class weka.gui.beans.InteractiveTableModel

getColumnCount() - Method in class weka.gui.SortedTableModel

Returns the number of columns in the model

getColumnCount() - Method in class weka.gui.sql.ResultSetHelper

returns the number of columns in the resultset.

getColumnCount() - Method in class weka.gui.sql.ResultSetTableModel

returns the number of columns in the model.

getColumnDimension() - Method in class weka.core.matrix.Matrix

Get column dimension.

getColumnName(int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the name of the column at columnIndex

getColumnName(int) - Method in class weka.gui.beans.InteractiveTableModel

getColumnName(int) - Method in class weka.gui.SortedTableModel

Returns the name of the column at columnIndex

getColumnName(int) - Method in class weka.gui.sql.ResultSetTableModel

returns the name of the column at columnIndex.

getColumnNames() - Method in class weka.gui.sql.ResultSetHelper

returns an array with the names of the columns in the resultset.

getColumnPackedCopy() - Method in class weka.core.matrix.Matrix

Make a one-dimensional column packed copy of the internal array.

getCombinationRule() - Method in class weka.classifiers.meta.Vote

Gets the combination rule used

getCommand() - Method in class weka.gui.treevisualizer.TreeDisplayEvent

getComment() - Method in enum weka.core.TechnicalInformation.Field

returns the comment string

getComment() - Method in enum weka.core.TechnicalInformation.Type

returns the comment string

getCommonPrefix() - Method in class weka.core.Trie

returns the common prefix for all the nodes

getCommonPrefix() - Method in class weka.core.Trie.TrieNode

returns the common prefix for all the nodes starting with this node.

getCommonPrefix(String) - Method in class weka.core.Trie.TrieNode

returns the common prefix for all the nodes starting with the node for the specified prefix.

getCommonPrefix(Vector<String>) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns the common prefix for all the items in the list.

getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the compareFunction property.

getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the compareFunction property.

getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.KNNInput

Gets the value of the compareFunction property.

getComparison() - Method in class weka.associations.NumericItem

Gets the comparison operator for this item.

getComparisonAsString() - Method in class weka.associations.Item

Get this item's comparison operator as a String.

getComparisonAsString() - Method in class weka.associations.NominalItem

Get this item's comparison operator as a String.

getComparisonAsString() - Method in class weka.associations.NumericItem

Get this item's comparison operator as a String.

getComparisonField() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the name of the field used for comparison.

getComparisons() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the comparisons property.

getCompatibilityState() - Method in class weka.experiment.AveragingResultProducer

Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).

getCompatibilityState() - Method in class weka.experiment.CrossValidationResultProducer

getCompatibilityState() - Method in class weka.experiment.DatabaseResultProducer

getCompatibilityState() - Method in class weka.experiment.ExplicitTestsetResultProducer

getCompatibilityState() - Method in class weka.experiment.LearningRateResultProducer

getCompatibilityState() - Method in class weka.experiment.RandomSplitResultProducer

getCompatibilityState() - Method in interface weka.experiment.ResultProducer

getComponent() - Method in class weka.gui.visualize.JComponentWriter

returns the component that is stored in the output format

getComponent() - Method in class weka.gui.visualize.PrintableComponent

returns the GUI component this print dialog is part of.

getComposite() - Method in class weka.gui.visualize.PostscriptGraphics

getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the compoundPredicate property.

getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the compoundPredicate property.

getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the compoundPredicate property.

getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the compoundPredicate property.

getCompressOutput() - Method in class weka.core.converters.ArffSaver

Gets whether the output data is compressed.

getCompressOutput() - Method in class weka.core.converters.JSONSaver

Gets whether the output data is compressed.

getCompressOutput() - Method in class weka.core.converters.XRFFSaver

Gets whether the output data is compressed.

getCon() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the con property.

getConfidence() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the confidence property.

getConfidence() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Gets the value of the confidence property.

getConfidence() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the confidence property.

getConfidence() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the confidence property.

getConfidenceFactor() - Method in class weka.classifiers.rules.PART

Get the value of CF.

getConfidenceFactor() - Method in class weka.classifiers.trees.J48

Get the value of CF.

getConfidenceLevel() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the confidenceLevel property.

getConfidenceLowerBound() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the confidenceLowerBound property.

getConfidenceUpperBound() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the confidenceUpperBound property.

getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewer

returns the setting of whether to display a confirm messagebox or not on exit

getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the setting of whether to display a confirm messagebox or not on exit

getConfusionMatrix() - Method in class weka.classifiers.evaluation.TwoClassStats

Generates a ConfusionMatrix representing the current two-class statistics, using class names "negative" and "positive".

getConfusionMatrix() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the confusionMatrix property.

getConnectedFormat() - Method in class weka.gui.beans.ClassAssigner

Returns the structure of the incoming instances (if any)

getConnectedFormat() - Method in class weka.gui.beans.ClassValuePicker

Returns the structure of the incoming instances (if any)

getConnectedFormat() - Method in class weka.gui.beans.FlowByExpression

Returns the structure of the incoming instances (if any)

getConnectedFormat() - Method in class weka.gui.beans.Sorter

Returns the structure of the incoming instances (if any)

getConnection() - Method in class weka.gui.sql.DbUtils

returns the current database connection.

getConnections(Integer...) - Static method in class weka.gui.beans.BeanConnection

Returns the list of connections

getConnectorPoint(int) - Method in class weka.gui.beans.BeanVisual

Returns the coordinates of the connector point given a compass point

getConsequence() - Method in class weka.associations.AssociationRule

Get the consequence of this rule.

getConsequence() - Method in class weka.associations.DefaultAssociationRule

getConsequenceSupport() - Method in class weka.associations.AssociationRule

Get the support for the consequence.

getConsequenceSupport() - Method in class weka.associations.DefaultAssociationRule

getConsequent() - Method in class weka.classifiers.rules.JRip.RipperRule

Gets the internal representation of the class label to be predicted

getConsequent() - Method in class weka.classifiers.rules.Rule

Get the consequent of this rule, i.e.

getConsequent() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the consequent property.

getConservativeForwardSelection() - Method in class weka.attributeSelection.GreedyStepwise

Gets whether conservative selection has been enabled

getConstant() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the constant property.

getConstant() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the constant property.

getConstant() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the constant property.

getConsumeNonMatching() - Method in class weka.gui.beans.SubstringLabeler

Get whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.

getConsumeNonMatching() - Method in class weka.gui.beans.SubstringLabelerRules

Get whether to consume non matching instances.

getContainChildBalls() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Gets whether if a parent ball should completely enclose its two child balls.

getContent(Element) - Method in class weka.classifiers.bayes.net.BIFReader

Returns all TEXT children of the given node in one string.

getContent(Element) - Method in class weka.classifiers.bayes.net.EditableBayesNet

XML helper function.

getContent() - Method in class weka.core.pmml.jaxbbindings.Annotation

Gets the value of the content property.

getContent() - Method in class weka.core.pmml.jaxbbindings.ArrayType

Gets the value of the content property.

getContent() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.Extension

Gets the value of the content property.

getContent() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.MiningModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.Node

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.Row

Gets the value of the content property.

getContent() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the rest of the content model.

getContent() - Method in class weka.core.pmml.jaxbbindings.Timestamp

Gets the value of the content property.

getContent() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the rest of the content model.

getContent(Element) - Static method in class weka.core.xml.XMLDocument

returns the text between the opening and closing tag of a node (performs a trim() on the result).

getContent() - Method in class weka.gui.scripting.Script

Returns the content.

getContinuousScoringMethod() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the continuousScoringMethod property.

getContrastMatrixType() - Method in class weka.core.pmml.jaxbbindings.Predictor

Gets the value of the contrastMatrixType property.

getControlPanel() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

This method returns a handle to the extra controls panel, so that the visualizing class can add it to some of it's own gui panel.

getControlPanel() - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method returns the extra controls panel for the LayoutEngine, if there is any.

getContStats() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the contStats property.

getConvertNominal() - Method in class weka.classifiers.trees.LMT

Get the value of convertNominal.

getCoord1() - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Gets the value of the coord1 property.

getCoord2() - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Gets the value of the coord2 property.

getCoord3() - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Gets the value of the coord3 property.

getCopyright() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the copyright property.

getCoreConvertersOnly() - Method in class weka.gui.ConverterFileChooser

Returns whether only the hardcoded core converters are displayed.

getCorrelationFields() - Method in class weka.core.pmml.jaxbbindings.Correlations

Gets the value of the correlationFields property.

getCorrelationMatrix() - Method in class weka.attributeSelection.PrincipalComponents

Return the correlation/covariance matrix

getCorrelationMethods() - Method in class weka.core.pmml.jaxbbindings.Correlations

Gets the value of the correlationMethods property.

getCorrelations() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation

Gets the value of the correlations property.

getCorrelationValues() - Method in class weka.core.pmml.jaxbbindings.Correlations

Gets the value of the correlationValues property.

getCostMatrix() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Gets the misclassification cost matrix.

getCostMatrixSource() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Gets the source location method of the cost matrix.

getCount(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Get a counts for a value

getCount() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Gets the value of the count property.

getCount() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount

Gets the value of the count property.

getCount() - Method in class weka.core.pmml.jaxbbindings.TimeException

Gets the value of the count property.

getCount(double) - Method in class weka.estimators.DiscreteEstimator

Get the count for a value

getCount(int) - Method in class weka.experiment.ResultMatrix

returns the count for the row.

getCount(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the number of visible nodes there are (this may accidentally count some of the invis nodes).

getCounts(int[], int[], int[], int, int, boolean) - Method in class weka.classifiers.bayes.net.ADNode

get counts for specific instantiation of a set of nodes

getCounts(int[], int[], int[], int, int, ADNode, boolean) - Method in class weka.classifiers.bayes.net.VaryNode

get counts for specific instantiation of a set of nodes

getCounts() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the counts property.

getCounts() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the counts property.

getCountTable() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the countTable property.

getCountWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the counts.

getCovariance() - Method in class weka.estimators.MultivariateGaussianEstimator

getCovariances() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the covariances property.

getCover() - Method in class weka.classifiers.rules.JRip.Antd

getCreatorApplication() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get the name of the application that created this model

getCreatorApplication() - Method in interface weka.core.pmml.PMMLModel

Get the name of the application that created this model.

getCriterion() - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod

Gets the value of the criterion property.

getCrossVal() - Method in class weka.classifiers.rules.DecisionTable

Gets the number of folds for cross validation

getCrossValidate() - Method in class weka.classifiers.lazy.IBk

Gets whether hold-one-out cross-validation will be used to select the best k value.

getCumHazard() - Method in class weka.core.pmml.jaxbbindings.BaselineCell

Gets the value of the cumHazard property.

getCumulativeLink() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the cumulativeLink property.

getCurrent() - Method in class weka.core.Memory

returns the currently used size of the JVM heap, obtains a fresh MemoryUsage object to do so.

getCurrentBeanLayout() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getCurrentDatasetNumber() - Method in class weka.experiment.Experiment

When an experiment is running, this returns the current dataset number.

getCurrentDir() - Static method in class weka.core.Debug

returns the current working directory of the user

getCurrentFilename() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the filename of the current tab

getCurrentIndex() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the currently selected tab index

getCurrentInstance() - Method in class weka.gui.beans.IncrementalClassifierEvent

Get the current instance

getCurrentLogPanel() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getCurrentModel() - Method in class weka.classifiers.misc.SerializedClassifier

Gets the currently loaded model (can be null).

getCurrentPanel() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the currently selected panel

getCurrentPropertyNumber() - Method in class weka.experiment.Experiment

When an experiment is running, this returns the index of the current custom property value.

getCurrentRunNumber() - Method in class weka.experiment.Experiment

When an experiment is running, this returns the current run number.

getCurrentTabIndex() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getCurrentZoomSetting() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.CostCurve

Calculates the performance stats for the default class and return results as a set of Instances.

getCurve(ArrayList<Prediction>, int) - Method in class weka.classifiers.evaluation.CostCurve

Calculates the performance stats for the desired class and return results as a set of Instances.

getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.MarginCurve

Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.

getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.ThresholdCurve

Calculates the performance stats for the default class and return results as a set of Instances.

getCurve(ArrayList<Prediction>, int) - Method in class weka.classifiers.evaluation.ThresholdCurve

Calculates the performance stats for the desired class and return results as a set of Instances.

getCustomEditor() - Method in class weka.gui.beans.EnvironmentField

getCustomEditor() - Method in class weka.gui.CostMatrixEditor

Gets a GUI component with which the user can edit the cost matrix.

getCustomEditor() - Method in class weka.gui.FileEditor

Gets the custom editor component.

getCustomEditor() - Method in class weka.gui.GenericArrayEditor

Returns the array editing component.

getCustomEditor() - Method in class weka.gui.GenericObjectEditor

Returns the array editing component.

getCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor

Gets a GUI component with which the user can edit the date format.

getCustomHeight() - Method in class weka.gui.visualize.JComponentWriter

gets the custom height currently used

getCustomName() - Method in class weka.gui.beans.Appender

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Associator

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in interface weka.gui.beans.BeanCommon

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.ClassAssigner

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Classifier

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.ClassValuePicker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Clusterer

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.CostBenefitAnalysis

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.CrossValidationFoldMaker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.DataVisualizer

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Filter

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.FlowByExpression

getCustomName() - Method in class weka.gui.beans.ImageSaver

getCustomName() - Method in class weka.gui.beans.ImageViewer

getCustomName() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Join

Get the custom name of this step

getCustomName() - Method in class weka.gui.beans.Loader

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.MetaBean

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.ModelPerformanceChart

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.PredictionAppender

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Saver

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.SerializedModelSaver

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.Sorter

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.StripChart

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.SubstringLabeler

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.SubstringReplacer

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.TestSetMaker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.TextSaver

getCustomName() - Method in class weka.gui.beans.TextViewer

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.TrainingSetMaker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomName() - Method in class weka.gui.beans.TrainTestSplitMaker

Get the custom (descriptive) name for this bean (if one has been set)

getCustomPanel() - Method in class weka.gui.beans.EnvironmentField

getCustomPanel() - Method in interface weka.gui.CustomPanelSupplier

Gets the custom panel for the object.

getCustomPanel() - Method in class weka.gui.GenericObjectEditor

Gets the custom panel used for editing the object.

getCustomPropsFile() - Method in class weka.core.converters.DatabaseLoader

Returns the custom properties file in use, if any.

getCustomPropsFile() - Method in class weka.core.converters.DatabaseSaver

Returns the custom properties file in use, if any.

getCustomPropsFile() - Method in class weka.experiment.InstanceQuery

Returns the custom properties file in use, if any.

getCustomWidth() - Method in class weka.gui.visualize.JComponentWriter

gets the custom width currently used

getCutoff() - Method in class weka.clusterers.Cobweb

get the cutoff

getCutPoints(int) - Method in class weka.filters.supervised.attribute.Discretize

Gets the cut points for an attribute

getCutPoints(int) - Method in class weka.filters.unsupervised.attribute.Discretize

Gets the cut points for an attribute

getCVisible() - Method in class weka.gui.treevisualizer.Node

Get If this node's childs are visible.

getCVParameter(int) - Method in class weka.classifiers.meta.CVParameterSelection

Gets the scheme paramter with the given index.

getCVParameters() - Method in class weka.classifiers.meta.CVParameterSelection

Get method for CVParameters.

getCVPredictions(Classifier, Instances, int) - Method in class weka.classifiers.evaluation.EvaluationUtils

Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.

getCVType() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

get cross validation strategy to be used in searching for networks.

getD() - Method in class weka.core.matrix.EigenvalueDecomposition

Return the block diagonal eigenvalue matrix

getD00Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the d00Parameter property.

getD01Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the d01Parameter property.

getD10Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the d10Parameter property.

getD11Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the d11Parameter property.

getData() - Method in class weka.attributeSelection.BestFirst.Link2

Get a group

getData() - Method in class weka.classifiers.rules.RuleStats

Get the data of the stats

getData() - Method in class weka.core.AttributeLocator

returns the underlying data

getData() - Method in class weka.core.converters.ArffLoader.ArffReader

Returns the data that was read

getData() - Method in class weka.core.TestInstances

returns the current dataset, can be null

getDatabaseURL() - Method in class weka.experiment.DatabaseUtils

Get the value of DatabaseURL.

getDataDictionary() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get the data dictionary.

getDataDictionary() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the dataDictionary property.

getDataFields() - Method in class weka.core.pmml.jaxbbindings.DataDictionary

Gets the value of the dataField property.

getDataFileName() - Method in class weka.classifiers.BVDecompose

Get the name of the data file used for the decomposition

getDataFileName() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the name of the data file used for the decomposition

getDataName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Gets the value of the dataName property.

getDataName() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the dataName property.

getDataPoint() - Method in class weka.gui.beans.ChartEvent

Get the data point

getDataset() - Method in class weka.classifiers.CheckSource

Gets the dataset to use for testing, can be null.

getDataSet() - Method in class weka.core.converters.AbstractLoader

getDataSet() - Method in class weka.core.converters.ArffLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.C45Loader

Return the full data set.

getDataSet() - Method in class weka.core.converters.ConverterUtils.DataSource

returns the full dataset, can be null in case of an error.

getDataSet(int) - Method in class weka.core.converters.ConverterUtils.DataSource

returns the full dataset with the specified class index set, can be null in case of an error.

getDataSet() - Method in class weka.core.converters.CSVLoader

getDataSet() - Method in class weka.core.converters.DatabaseLoader

Return the full data set in batch mode (header and all intances at once).

getDataSet() - Method in class weka.core.converters.JSONLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.LibSVMLoader

Return the full data set.

getDataSet() - Method in interface weka.core.converters.Loader

Return the full data set.

getDataSet() - Method in class weka.core.converters.MatlabLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.SerializedInstancesLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.SVMLightLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.TextDirectoryLoader

Return the full data set.

getDataSet() - Method in class weka.core.converters.XRFFLoader

Return the full data set.

getDataset() - Method in class weka.filters.CheckSource

Gets the dataset to use for testing, can be null.

getDataSet() - Method in class weka.gui.beans.DataSetEvent

Return the instances of the data set

getDataSet() - Method in class weka.gui.beans.ThresholdDataEvent

Return the instances of the data set

getDataSet() - Method in class weka.gui.beans.VisualizableErrorEvent

Return the instances of the data set

getDatasetFormat() - Method in class weka.datagenerators.DataGenerator

Gets the format of the dataset that is to be generated.

getDatasetKeyColumns() - Method in class weka.experiment.PairedTTester

Get the value of DatasetKeyColumns.

getDatasetKeyColumns() - Method in interface weka.experiment.Tester

Get the value of DatasetKeyColumns.

getDatasets() - Method in class weka.experiment.Experiment

Gets the datasets in the experiment.

getDatasetsFirst() - Static method in class weka.gui.experiment.ExperimenterDefaults

whether datasets or algorithms are iterated first.

getDataType() - Method in class weka.core.pmml.jaxbbindings.Constant

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.ParameterField

Gets the value of the dataType property.

getDataType() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the dataType property.

getDataType() - Method in class weka.gui.beans.xml.XMLBeans

returns the type of data that is to be read/written

getDataUsage() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the dataUsage property.

getDateAttributes() - Method in class weka.core.converters.CSVLoader

Returns the current attribute range to be forced to type date.

getDateFormat() - Method in class weka.core.Attribute

Returns the Date format pattern in case this attribute is of type DATE, otherwise an empty string.

getDateFormat() - Method in class weka.core.converters.CSVLoader

Get the format to use for parsing date values.

getDateFormat() - Method in class weka.filters.unsupervised.attribute.Add

Get the date format, complying to ISO-8601.

getDateFormat() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the date formatting string (if any)

getDateFormat() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Get the date format used in output.

getDateFormat() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Get the date format to use for parsing the date replacement constant

getDateReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Get the date replacement value

getDateValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the value of the attribute as a date or null if the attribute isn't of type date.

getDbUtils() - Method in class weka.gui.sql.event.ConnectionEvent

returns the DbUtils instance that is responsible for the connect/disconnect.

getDbUtils() - Method in class weka.gui.sql.event.QueryExecuteEvent

returns the DbUtils instance that was executed the query

getDebug() - Method in class weka.attributeSelection.CfsSubsetEval

Set whether to output debugging info

getDebug() - Method in class weka.classifiers.AbstractClassifier

Get whether debugging is turned on.

getDebug() - Method in class weka.classifiers.BVDecompose

Gets whether debugging is turned on

getDebug() - Method in class weka.classifiers.BVDecomposeSegCVSub

Gets whether debugging is turned on

getDebug() - Method in class weka.classifiers.functions.Logistic

Gets whether debugging output will be printed.

getDebug() - Method in class weka.classifiers.functions.supportVector.Kernel

Gets whether debugging output is turned on or not.

getDebug() - Method in class weka.classifiers.meta.MultiScheme

Get whether debugging is turned on

getDebug() - Method in class weka.classifiers.rules.JRip

Gets whether debug information is output to the console

getDebug() - Method in class weka.clusterers.AbstractClusterer

Get whether debugging is turned on.

getDebug() - Method in class weka.clusterers.EM

Get debug mode

getDebug() - Method in class weka.core.Check

Get whether debugging is turned on

getDebug() - Method in class weka.core.converters.TextDirectoryLoader

Gets whether additional debug information is printed.

getDebug() - Method in class weka.core.Debug.Random

returns whether to print the generated random values or not

getDebug() - Method in class weka.datagenerators.DataGenerator

Gets the debug flag.

getDebug() - Method in class weka.estimators.CheckEstimator

Get whether debugging is turned on

getDebug() - Method in class weka.estimators.Estimator

Get whether debugging is turned on.

getDebug() - Method in class weka.experiment.DatabaseUtils

Gets whether there should be printed some debugging output to stderr or not.

getDebug() - Method in interface weka.experiment.InstanceQueryAdapter

Gets whether there should be printed some debugging output to stderr or not.

getDebug() - Method in class weka.filters.SimpleFilter

Get whether debugging is turned on.

getDebug() - Method in class weka.filters.unsupervised.attribute.AddExpression

Gets whether debug is set

getDebug() - Method in class weka.gui.DatabaseConnectionDialog

Returns the debug flag

getDebug() - Method in class weka.gui.scripting.ScriptingPanel

Returns whether debugging mode is on.

getDebug() - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns whether debug mode is on.

getDebug() - Method in class weka.gui.streams.InstanceCounter

getDebug() - Method in class weka.gui.streams.InstanceJoiner

getDebug() - Method in class weka.gui.streams.InstanceLoader

getDebug() - Method in class weka.gui.streams.InstanceSavePanel

getDebug() - Method in class weka.gui.streams.InstanceTable

getDebug() - Method in class weka.gui.streams.InstanceViewer

getDebuggingOutput() - Method in class weka.attributeSelection.GreedyStepwise

Get whether to output debugging info to the console

getDecay() - Method in class weka.classifiers.functions.MultilayerPerceptron

getDecimals() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the number of decimals to round to.

getDecision() - Method in class weka.core.pmml.jaxbbindings.Decisions

Gets the value of the decision property.

getDecisions() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the decisions property.

getDefault() - Method in class weka.core.Tee

returns the default printstrean, can be NULL.

getDefaultChild() - Method in class weka.core.pmml.jaxbbindings.Node

Gets the value of the defaultChild property.

getDefaultColNameWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the column names.

getDefaultColNameWidth() - Method in class weka.experiment.ResultMatrixGnuPlot

returns the default width for the column names.

getDefaultConfidence() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the defaultConfidence property.

getDefaultCountWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the counts.

getDefaultCountWidth() - Method in class weka.experiment.ResultMatrixPlainText

returns the default width for the counts.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrix

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixCSV

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixGnuPlot

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixHTML

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixLatex

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateRowNames() - Method in class weka.experiment.ResultMatrix

returns theh default of whether row names are prefixed with the index.

getDefaultEnumerateRowNames() - Method in class weka.experiment.ResultMatrixGnuPlot

returns the default of whether row names are prefixed with the index.

getDefaultExtension() - Method in class weka.gui.scripting.GroovyScript

Returns the default extension.

getDefaultExtension() - Method in class weka.gui.scripting.JythonScript

Returns the default extension.

getDefaultExtension() - Method in class weka.gui.scripting.Script

Returns the default extension.

getDefaultMeanPrec() - Method in class weka.experiment.ResultMatrix

returns the default precision for the means.

getDefaultMeanWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the mean.

getDefaultNumDecimals() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the default number of digits to output after the decimal point.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrix

returns the default of whether column names or numbers instead are printed.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixCSV

returns the default of whether column names or numbers instead are printed.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixHTML

returns the default of whether column names or numbers instead are printed.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixLatex

returns the default of whether column names or numbers instead are printed.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixSignificance

returns the default of whether column names or numbers instead are printed.

getDefaultPrintRowNames() - Method in class weka.experiment.ResultMatrix

returns the default of whether row names or numbers instead are printed.

getDefaultRemoveFilterName() - Method in class weka.experiment.ResultMatrix

returns the default of whether the filter classname is removed from the dataset name.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixCSV

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixGnuPlot

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixHTML

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixPlainText

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixSignificance

returns the default width for the row names.

getDefaultScore() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the defaultScore property.

getDefaultShowAverage() - Method in class weka.experiment.ResultMatrix

returns the default of whether average per column is displayed or not.

getDefaultShowStdDev() - Method in class weka.experiment.ResultMatrix

returns the default of whether std deviations are displayed or not.

getDefaultShowStdDev() - Method in class weka.experiment.ResultMatrixSignificance

returns the default of whether std deviations are displayed or not.

getDefaultSignificanceWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the significance.

getDefaultStdDevPrec() - Method in class weka.experiment.ResultMatrix

returns the default standard deviation precision.

getDefaultStdDevWidth() - Method in class weka.experiment.ResultMatrix

returns the default width for the std dev.

getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the defaultValue property.

getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Gets the value of the defaultValue property.

getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the defaultValue property.

getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Gets the value of the defaultValue property.

getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the defaultValue property.

getDefaultValue() - Method in class weka.core.pmml.TargetMetaInfo

Get the default value (numeric target)

getDefineFunction() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary

Gets the value of the defineFunction property.

getDegree() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Gets the value of the degree property.

getDegreesOfFreedom() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the degreesOfFreedom property.

getDegreesOfFreedom() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the degreesOfFreedom property.

getDegreesOfFreedom() - Method in class weka.experiment.PairedStats

Gets the degrees of freedom.

getDeleteEmptyBins() - Method in class weka.classifiers.meta.RegressionByDiscretization

Gets whether empty bins are deleted.

getDelimiter() - Method in class weka.core.pmml.jaxbbindings.Delimiter

Gets the value of the delimiter property.

getDelimiters() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer

Get the value of delimiters (not backquoted).

getDelimiters() - Method in class weka.gui.scripting.SyntaxDocument

Returns the delimiter characters to use.

getDelta() - Method in class weka.associations.Apriori

Get the value of delta.

getDelta() - Method in class weka.associations.FPGrowth

Get the value of delta.

getDelta() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

getDelta() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

getDelta() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the delta property.

getDensityBasedClusterer() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Get the clusterer used by this filter

getDerivedField() - Method in class weka.core.pmml.jaxbbindings.BayesInput

Gets the value of the derivedField property.

getDerivedField() - Method in class weka.core.pmml.jaxbbindings.LocalTransformations

Gets the value of the derivedField property.

getDerivedField() - Method in class weka.core.pmml.jaxbbindings.NeuralInput

Gets the value of the derivedField property.

getDerivedField() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput

Gets the value of the derivedField property.

getDerivedField() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary

Gets the value of the derivedField property.

getDerivedFields() - Method in class weka.core.pmml.MiningSchema

getDerivedValue(double[]) - Method in class weka.core.pmml.DerivedFieldMetaInfo

Get the derived field value for the given incoming vector of values.

getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getDescription() - Method in class weka.core.pmml.jaxbbindings.Decision

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.Decisions

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.LinearKernelType

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType

Gets the value of the description property.

getDescription() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Gets the value of the description property.

getDescription() - Method in class weka.gui.ExtensionFileFilter

Gets the description of accepted files.

getDescription() - Method in class weka.gui.visualize.BMPWriter

returns the name of the writer, to display in the FileChooser.

getDescription() - Method in class weka.gui.visualize.JComponentWriter

returns the name of the writer, to display in the FileChooser.

getDescription() - Method in class weka.gui.visualize.JPEGWriter

returns the name of the writer, to display in the FileChooser.

getDescription() - Method in class weka.gui.visualize.PNGWriter

returns the name of the writer, to display in the FileChooser.

getDescription() - Method in class weka.gui.visualize.PostscriptWriter

returns the name of the writer, to display in the FileChooser.

getDesignVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin

Get the specific version of Weka the class is designed for.

getDesiredWeightOfInstancesPerInterval() - Method in class weka.filters.unsupervised.attribute.Discretize

Get the DesiredWeightOfInstancesPerInterval value.

getDestination() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default destination.

getDetectionPerAttribute() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").

getDeviceConfiguration() - Method in class weka.gui.visualize.PostscriptGraphics

getDF() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the df property.

getDf() - Method in class weka.core.pmml.jaxbbindings.PCell

Gets the value of the df property.

getDiagDefault() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the diagDefault property.

getDictionary() - Method in class weka.classifiers.functions.SGDText

Get this model's dictionary (including term weights).

getDictionarySize() - Method in class weka.classifiers.functions.SGDText

Return the size of the dictionary (minus any low frequency terms that are below the threshold but haven't been pruned yet).

getDir() - Method in class weka.core.Javadoc

returns the current dir containing the class to update.

getDir() - Method in class weka.gui.Loader

returns the dir prefix

getDirection() - Method in class weka.attributeSelection.BestFirst

Get the search direction

getDirectory() - Method in class weka.core.converters.TextDirectoryLoader

get the Dir specified as the source

getDirectory() - Method in class weka.gui.beans.SerializedModelSaver

Get the directory that the model(s) will be saved into

getDiscardPredictions() - Method in class weka.classifiers.evaluation.Evaluation

Returns whether predictions are not recorded at all, in order to conserve memory.

getDiscardPredictions() - Method in class weka.classifiers.Evaluation

Returns whether predictions are not recorded at all, in order to conserve memory.

getDiscretize() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the discretize property.

getDiscretize() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the discretize property.

getDiscretize() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the discretize property.

getDiscretizeBin() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the discretizeBin property.

getDiscretizer() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Return the discretizer used at this node

getDiscrStats() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the discrStats property.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.CSV

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.HTML

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.Null

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.PlainText

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.XML

Returns a short display text, to be used in comboboxes.

getDisplay() - Method in enum weka.core.TechnicalInformation.Field

returns the display string

getDisplay() - Method in enum weka.core.TechnicalInformation.Type

returns the display string

getDisplayCol(int) - Method in class weka.experiment.ResultMatrix

returns the displayed index of the given col, depending on the order of columns, returns -1 if index out of bounds.

getDisplayedResultsets() - Method in class weka.experiment.PairedTTester

Gets the indices of the the datasets that are displayed (if null then all are displayed).

getDisplayedResultsets() - Method in interface weka.experiment.Tester

Gets the indices of the the datasets that are displayed (if null then all are displayed).

getDisplayModelInOldFormat() - Method in class weka.classifiers.bayes.NaiveBayes

Get whether to display model output in the old, original format.

getDisplayModelInOldFormat() - Method in class weka.clusterers.EM

Get whether to display model output in the old, original format.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the displayName property.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the displayName property.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the displayName property.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the displayName property.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the displayName property.

getDisplayName() - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Gets the value of the displayName property.

getDisplayName() - Method in class weka.experiment.PairedCorrectedTTester

returns the name of the tester

getDisplayName() - Method in class weka.experiment.PairedTTester

returns the name of the tester

getDisplayName() - Method in class weka.experiment.ResultMatrix

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixCSV

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixGnuPlot

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixHTML

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixLatex

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixPlainText

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixSignificance

returns the name of the output format.

getDisplayName() - Method in interface weka.experiment.Tester

returns the name of the testing algorithm

getDisplayRow(int) - Method in class weka.experiment.ResultMatrix

returns the displayed index of the given row, depending on the order of rows, returns -1 if index out of bounds.

getDisplayRules() - Method in class weka.classifiers.rules.DecisionTable

Gets whether rules are being printed

getDisplayStdDevs() - Method in class weka.clusterers.SimpleKMeans

Gets whether standard deviations and nominal count.

getDisplayValue() - Method in class weka.core.pmml.FieldMetaInfo.Value

getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.Decision

Gets the value of the displayValue property.

getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the displayValue property.

getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.Value

Gets the value of the displayValue property.

getDistanceFunction() - Method in class weka.clusterers.HierarchicalClusterer

getDistanceFunction() - Method in class weka.clusterers.SimpleKMeans

returns the distance function currently in use.

getDistanceFunction() - Method in class weka.core.neighboursearch.KDTree

returns the distance function currently in use.

getDistanceFunction() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

returns the distance function currently in use.

getDistanceIsBranchLength() - Method in class weka.clusterers.HierarchicalClusterer

getDistances() - Method in class weka.core.neighboursearch.BallTree

Returns the distances of the k nearest neighbours.

getDistances() - Method in class weka.core.neighboursearch.CoverTree

Returns the distances of the (k)-NN(s) found earlier by kNearestNeighbours()/nearestNeighbour().

getDistances() - Method in class weka.core.neighboursearch.KDTree

Returns the distances to the kNearest or 1 nearest neighbour currently found with either the kNearestNeighbours or the nearestNeighbour method.

getDistances() - Method in class weka.core.neighboursearch.LinearNNSearch

Returns the distances of the k nearest neighbours.

getDistances() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns the distances of the k nearest neighbours.

getDistanceWeighting() - Method in class weka.classifiers.lazy.IBk

Gets the distance weighting method used.

getDistMult() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the distance multiplier.

getDistParameter() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the distParameter property.

getDistribution(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)

getDistribution(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)

getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.HNode

Return a class probability distribution computed from the frequency counts at this node

getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.NBNode

getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.NBNodeAdaptive

getDistribution() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the distribution property.

getDistribution() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the current distribution that'll be used for calculating the random matrix

getDistributions() - Method in class weka.classifiers.bayes.BayesNet

Get full set of estimators.

getDistributions(int) - Method in class weka.classifiers.rules.RuleStats

Get the class distribution predicted by the rule in given position

getDistributionSpread() - Method in class weka.filters.supervised.instance.SpreadSubsample

Gets the value for the distribution spread

getDocType() - Method in class weka.core.xml.XMLDocument

returns the current DOCTYPE, can be null.

getDocument() - Method in class weka.core.xml.XMLDocument

returns the parsed DOM document.

getDocument() - Method in class weka.core.xml.XMLOptions

returns the parsed DOM document.

getDocument() - Method in class weka.gui.DocumentPrinting

Returns the document to print.

getDocumentNormalization() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Gets the value of the documentNormalization property.

getDoNotCheckCapabilities() - Method in class weka.classifiers.AbstractClassifier

Get whether capabilities checking is turned off.

getDoNotCheckCapabilities() - Method in class weka.clusterers.AbstractClusterer

Get whether capabilities checking is turned off.

getDoNotCheckCapabilities() - Method in class weka.filters.SimpleFilter

Get whether capabilities checking is turned off.

getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.rules.PART

Gets the value of doNotMakeSplitPointActualValue.

getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.trees.J48

Gets the value of doNotMakeSplitPointActualValue.

getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.trees.LMT

Gets the value of doNotMakeSplitPointActualValue.

getDoNotOperateOnPerClassBasis() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Get the DoNotOperateOnPerClassBasis value.

getDoNotPrintModels() - Method in class weka.classifiers.meta.Vote

Get whether to print the individual ensemble models in the output

getDontCalculateOutOfBagError() - Method in class weka.classifiers.trees.RandomForest

Get whether to turn off the calculation of out of bag error

getDontFilterAfterFirstBatch() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.

getDontNormalize() - Method in class weka.classifiers.functions.SGD

Get whether normalization has been turned off.

getDontNormalize() - Method in class weka.core.NormalizableDistance

Gets whether if the attribute values are to be normazlied in distance calculation.

getDontReplaceMissing() - Method in class weka.classifiers.functions.SGD

Get whether global replacement of missing values has been disabled.

getDontReplaceMissingValues() - Method in class weka.clusterers.Canopy

Gets whether missing values are to be replaced.

getDontReplaceMissingValues() - Method in class weka.clusterers.SimpleKMeans

Gets whether missing values are to be replaced.

getDontShowDialog(String) - Static method in class weka.core.Utils

For a named dialog, returns true if the user has opted not to view it again in the future.

getDontShowDialogResponse(String) - Static method in class weka.core.Utils

For a named dialog, if the user has opted not to view it again, returns the answer the answer the user supplied when they closed the dialog.

getDoublePivot() - Method in class weka.core.matrix.LUDecomposition

Return pivot permutation vector as a one-dimensional double array

getEditedStatus() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

Get the edited status of the currently selected tab.

getEditedStatus(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

Get the edited status of the tab at the supplied index.

getEditor() - Method in class weka.gui.PropertyDialog

Gets the current property editor.

getEditorActive() - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel

Returns true if the editor is currently in an active status---that is the array is active and able to be edited.

getEigenValues() - Method in class weka.attributeSelection.PrincipalComponents

Return the eigenvalues corresponding to the eigenvectors

getElement(int, int) - Method in class weka.classifiers.CostMatrix

Return the value of a cell as a double (for legacy code)

getElement(int, int, Instance) - Method in class weka.classifiers.CostMatrix

Return the value of a cell as a double.

getElement(int) - Method in class weka.core.AlgVector

Returns the value of a cell in the matrix.

getElement(int, int) - Method in class weka.core.Matrix

Deprecated. Returns the value of a cell in the matrix.

getElementAt(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Returns the component at the specified index.

getElements() - Method in class weka.core.AlgVector

Gets the elements of the vector and returns them as double array.

getEliminateColinearAttributes() - Method in class weka.classifiers.functions.LinearRegression

Get the value of EliminateColinearAttributes.

getEnabled() - Method in class weka.core.Debug

returns whether the logging is enabled

getEnclosureCharacters() - Method in class weka.core.converters.CSVLoader

Get the character(s) to use/recognize as string enclosures

getEndTime() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the endTime property.

getEndTimeVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the endTimeVariable property.

getEntropicAutoBlend() - Method in class weka.classifiers.lazy.KStar

Get whether entropic blending being used

getEntry(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Returns the table entry to which the specified key is mapped in this hashtable.

getEnumerateColNames() - Method in class weka.experiment.ResultMatrix

returns whether column names are prefixed with the index.

getEnumerateRowNames() - Method in class weka.experiment.ResultMatrix

returns whether row names or prefixed with the index.

getEnvironment() - Method in class weka.gui.beans.FlowRunner

Get the environment variables that are in use.

getEnvironmentSettings() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getEnvironmentSettings(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getEpochs() - Method in class weka.classifiers.functions.SGD

Get current number of epochs

getEpochs() - Method in class weka.classifiers.functions.SGDText

Get current number of epochs

getEpsilon() - Method in class weka.classifiers.functions.SGD

Get the epsilon threshold on the error for epsilon insensitive and Huber loss functions

getEpsilon() - Method in class weka.classifiers.functions.SMO

Get the value of epsilon.

getEpsilon() - Method in class weka.classifiers.functions.supportVector.RegSMO

Get the value of epsilon.

getEpsilonParameter() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Get the value of epsilon parameter of the epsilon insensitive loss function.

getError() - Method in class weka.classifiers.BVDecompose

Get the calculated error rate

getError() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated error rate

getErrorOnProbabilities() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of errorOnProbabilities.

getErrorOnProbabilities() - Method in class weka.classifiers.trees.LMT

Get the value of errorOnProbabilities.

getErrorPlotPointSizeProportionalToMargin() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Get whether the point size on classification error plots should be proportional to the prediction margin.

getErrors() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Return the errors made by the naive bayes model at this node

getErrors() - Method in class weka.classifiers.trees.j48.NBTreeSplit

Return the errors made by the naive bayes models arising from this split.

getEstimatedErrorsForLeaf() - Method in class weka.classifiers.rules.part.C45PruneableDecList

Computes estimated errors for leaf.

getEstimator() - Method in class weka.classifiers.bayes.BayesNet

Get the BayesNetEstimator used for calculating the CPTs

getEstimator() - Method in class weka.estimators.CheckEstimator

Get the estimator used as the estimator

getEstimator(double) - Method in interface weka.estimators.ConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.DDConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.DKConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.DNConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.KDConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.KKConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.NDConditionalEstimator

Get a probability estimator for a value

getEstimator(double) - Method in class weka.estimators.NNConditionalEstimator

Get a probability estimator for a value

getEstimatorType() - Method in class weka.classifiers.meta.RegressionByDiscretization

Get the estimator type

getEuclidean() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the euclidean property.

getEvaluation() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Returns the Evaluation object in use.

getEvaluationMeasure() - Method in class weka.attributeSelection.WrapperSubsetEval

Gets the currently set performance evaluation measure used for selecting attributes for the decision table

getEvaluationMeasure() - Method in class weka.classifiers.rules.DecisionTable

Gets the currently set performance evaluation measure used for selecting attributes for the decision table

getEvaluationMetric() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Get the evaluation metric to use

getEvaluationMetricsToOutput() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Get the evaluation metrics to output (as a comma-separated list).

getEvaluator() - Method in class weka.attributeSelection.CheckAttributeSelection

Get the current evaluator

getEvaluator() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Gets the attribute evaluator used

getEvaluator() - Method in class weka.filters.supervised.attribute.AttributeSelection

Get the name of the attribute/subset evaluator

getEvalUsingTrainingData() - Method in class weka.attributeSelection.OneRAttributeEval

Returns true if the training data is to be used for evaluation

getEventName() - Method in class weka.gui.beans.BeanConnection

Returns the name of the event for this conncetion

getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSinkBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSourceBeanInfo

Get the event set descriptors pertinent to data sources

getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTestSetProducerBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainingSetProducerBeanInfo

Returns event set descriptors for this type of bean

getEventSetDescriptors() - Method in class weka.gui.beans.AppenderBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.AssociatorBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.AttributeSummarizerBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.ClustererBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.CostBenefitAnalysisBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.DataVisualizerBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.FilterBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.FlowByExpressionBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.GraphViewerBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.ImageSaverBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.ImageViewerBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.InstanceStreamToBatchMakerBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.JoinBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.ModelPerformanceChartBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.NoteBeanInfo

getEventSetDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo

Get the event set descriptors pertinent to data sources

getEventSetDescriptors() - Method in class weka.gui.beans.ScatterPlotMatrixBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.SerializedModelSaverBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.SorterBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.SubstringLabelerBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.SubstringReplacerBeanInfo

Returns the event set descriptors

getEventSetDescriptors() - Method in class weka.gui.beans.TextSaverBeanInfo

Get the event set descriptors for this bean

getEventSetDescriptors() - Method in class weka.gui.beans.TextViewerBeanInfo

Get the event set descriptors for this bean

getEvidence(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

get evidence state of a node.

getException() - Method in class weka.gui.sql.event.ConnectionEvent

returns the stored exception, if any (can be NULL)

getException() - Method in class weka.gui.sql.event.QueryExecuteEvent

returns the exception, if one happened, otherwise NULL

getExecuting() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getExecuting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getExecutionSlots() - Method in class weka.gui.beans.Classifier

Get the number of execution slots (threads) used to train models.

getExecutionSlots() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Get the number of execution slots to use.

getExecutionStatus() - Method in class weka.experiment.TaskStatusInfo

Get the execution status of this Task.

getExecutionThread() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getExecutionThread(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getExitIfNoWindowsOpen() - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Gets whether System.exit gets called after the last window gets closed

getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewer

returns TRUE if a System.exit(0) is done on a close

getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns TRUE if a System.exit(0) is done on a close

getExpectedResultsPerAverage() - Method in class weka.experiment.AveragingResultProducer

Get the value of ExpectedResultsPerAverage.

getExperiment() - Method in class weka.experiment.RemoteExperimentSubTask

Get the experiment for this sub task

getExperiment() - Method in class weka.gui.experiment.SetupModePanel

Gets the currently configured experiment.

getExperiment() - Method in class weka.gui.experiment.SetupPanel

Gets the currently configured experiment.

getExperiment() - Method in class weka.gui.experiment.SimpleSetupPanel

Gets the currently configured experiment.

getExperimentType() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default experiment type.

getExplicitPropsFile() - Method in class weka.gui.GenericPropertiesCreator

returns TRUE, if a file is loaded and not the Utils class used for locating the props file.

getExplorer() - Method in class weka.gui.explorer.AssociationsPanel

returns the parent Explorer frame

getExplorer() - Method in class weka.gui.explorer.AttributeSelectionPanel

returns the parent Explorer frame

getExplorer() - Method in class weka.gui.explorer.ClassifierPanel

returns the parent Explorer frame.

getExplorer() - Method in class weka.gui.explorer.ClustererPanel

returns the parent Explorer frame

getExplorer() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel

returns the parent Explorer frame

getExplorer() - Method in class weka.gui.explorer.PreprocessPanel

returns the parent Explorer frame

getExplorer() - Method in class weka.gui.explorer.VisualizePanel

returns the parent Explorer frame

getExponent() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Gets the exponent value.

getExponent() - Method in class weka.classifiers.functions.VotedPerceptron

Get the value of exponent.

getExponent() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the exponent property.

getExponent() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Gets the value of the exponent property.

getExpression(Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - Static method in class weka.core.pmml.Expression

Static factory method that returns a subclass of Expression that encapsulates the type of expression contained in the Element supplied.

getExpression(String, Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - Static method in class weka.core.pmml.Expression

Static factory method that returns a subclass of Expression that encapsulates the type of expression supplied as an argument.

getEXPRESSION() - Method in class weka.core.pmml.jaxbbindings.Apply

Gets the value of the expression property.

getExpression() - Method in class weka.datagenerators.classifiers.regression.Expression

Gets the mathematical expression for generating y out of x

getExpression() - Method in class weka.filters.unsupervised.attribute.AddExpression

Get the expression

getExpression() - Method in class weka.filters.unsupervised.attribute.MathExpression

Get the expression

getExpression() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Returns the regular expression in use.

getExpression() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Returns the expression used for filtering.

getExpressionString() - Method in class weka.gui.beans.FlowByExpression

Get the current expression (in internal format)

getExtender() - Method in class weka.core.pmml.jaxbbindings.Extension

Gets the value of the extender property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Aggregate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Alternate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Anova

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Application

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Apply

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BaselineCell

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesInput

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesInputs

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesOutput

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.BoundaryValues

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Categories

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Category

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Characteristic

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Characteristics

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Chebychev

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CityBlock

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ClassLabels

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Coefficient

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Coefficients

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Comparisons

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Con1

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ContStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationFields

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Correlations

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationValues

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Counts

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Covariances

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.CovariateList

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DataDictionary

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Decision

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Decisions

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Delimiter

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DiscrStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Euclidean

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.EventValues

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.FactorList

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.False

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldRef

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldValue

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.InlineTable

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.InstanceField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.InstanceFields

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Interval

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Item

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ItemRef

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Itemset

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Jaccard

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.KNNInput

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.KNNInputs

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.LinearKernelType

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.LinearNorm

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.LocalTransformations

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningBuildTask

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningSchema

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Minkowski

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralInput

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Output

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PairCounts

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Parameter

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ParameterList

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ParamMatrix

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Partition

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PCell

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PPCell

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PPMatrix

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Predictor

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Quantile

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Segmentation

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SequenceReference

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SetReference

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleMatching

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SquaredEuclidean

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVector

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TableLocator

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Tanimoto

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Targets

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValueCounts

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Taxonomy

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TextCorpus

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TextDictionary

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TextDocument

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Time

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.True

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.Value

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorFields

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.VerificationField

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.VerificationFields

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.XCoordinates

Gets the value of the extension property.

getExtension() - Method in class weka.core.pmml.jaxbbindings.YCoordinates

Gets the value of the extension property.

getExtension() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default experiment extension.

getExtension() - Method in class weka.gui.visualize.BMPWriter

returns the extension (incl.

getExtension() - Method in class weka.gui.visualize.JComponentWriter

returns the extension (incl.

getExtension() - Method in class weka.gui.visualize.JPEGWriter

returns the extension (incl.

getExtension() - Method in class weka.gui.visualize.PNGWriter

returns the extension (incl.

getExtension() - Method in class weka.gui.visualize.PostscriptWriter

returns the extension (incl.

getExtensionAndDelimiterAndTime() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the extensionAndDelimiterAndTime property.

getExtensions() - Method in class weka.gui.ExtensionFileFilter

Returns a copy of the acceptable extensions.

getExtremeValuesAsOutliers() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Get whether extreme values are also tagged as outliers.

getExtremeValuesFactor() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets the factor for determining the thresholds for extreme values.

getFactory() - Method in class weka.core.xml.XMLDocument

returns the DocumentBuilderFactory.

getFailReason() - Method in class weka.core.Capabilities

returns the reason why the tests failed, is null if tests succeeded

getFallout() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the fallout.

getFalse() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the false property.

getFalse() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the false property.

getFalse() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the false property.

getFalse() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the false property.

getFalseNegative() - Method in class weka.classifiers.evaluation.TwoClassStats

Gets the number of positive instances predicted as negative

getFalsePositive() - Method in class weka.classifiers.evaluation.TwoClassStats

Gets the number of negative instances predicted as positive

getFalsePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the false positive rate.

getFalseStepName() - Method in class weka.gui.beans.FlowByExpression

Get the name of the connected step to send "false" instances to

getFastDistanceCalc() - Method in class weka.clusterers.SimpleKMeans

Gets whether to use faster distance calculation.

getFastRegression() - Method in class weka.classifiers.trees.LMT

Get the value of fastRegression.

getFeature() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the feature property.

getFeature() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the feature property.

getField() - Method in class weka.core.pmml.jaxbbindings.Aggregate

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.FieldRef

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.FieldValue

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.InstanceField

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.KNNInput

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the field property.

getField() - Method in class weka.core.pmml.jaxbbindings.VerificationField

Gets the value of the field property.

getFieldAsAttribute() - Method in class weka.core.pmml.DerivedFieldMetaInfo

Get this derived field as an Attribute.

getFieldAsAttribute() - Method in class weka.core.pmml.FieldMetaInfo

Return this field as an Attribute.

getFieldAsAttribute() - Method in class weka.core.pmml.MiningFieldMetaInfo

Return this mining field as an Attribute.

getFieldAsAttribute() - Method in class weka.core.pmml.TargetMetaInfo

Return this field as an Attribute.

getFieldColumnPair() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the fieldColumnPair property.

getFieldCount() - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Gets the value of the fieldCount property.

getFieldCount() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the fieldCount property.

getFieldDef(String) - Method in class weka.core.pmml.Expression

Return the named attribute from the list of reference fields.

getFieldDefIndex(String) - Method in class weka.core.pmml.Expression

getFieldName() - Method in class weka.core.pmml.FieldMetaInfo

Get the name of this field.

getFieldName() - Method in class weka.core.pmml.jaxbbindings.BayesInput

Gets the value of the fieldName property.

getFieldName() - Method in class weka.core.pmml.jaxbbindings.BayesOutput

Gets the value of the fieldName property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the fieldRef property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the fieldRef property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the fieldRef property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the fieldRef property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Gets the value of the fieldRef property.

getFieldRef() - Method in class weka.core.pmml.jaxbbindings.VectorFields

Gets the value of the fieldRef property.

getFieldsAsInstances() - Method in class weka.core.pmml.MiningSchema

Get the all the fields (both mining schema and derived) as Instances.

getFieldSeparator() - Method in class weka.core.converters.CSVLoader

Returns the character used as column separator.

getFieldSeparator() - Method in class weka.core.converters.CSVSaver

Returns the character used as column separator.

getFieldsMappingString() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get a textual description of the mapping between mining schema fields and incoming data fields.

getFieldsMappingString() - Method in class weka.core.pmml.MappingInfo

Get a textual description of them mapping between mining schema fields and incoming data fields.

getFieldValue() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE

Gets the value of the fieldValue property.

getFieldValue() - Method in class weka.core.pmml.jaxbbindings.FieldValue

Gets the value of the fieldValue property.

getFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE

Gets the value of the fieldValueCount property.

getFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.FieldValue

Gets the value of the fieldValueCount property.

getFieldWeight() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the fieldWeight property.

getFieldWeight() - Method in class weka.core.pmml.jaxbbindings.KNNInput

Gets the value of the fieldWeight property.

getFile() - Method in class weka.core.pmml.jaxbbindings.TextDocument

Gets the value of the file property.

getFile() - Method in class weka.gui.visualize.JComponentWriter

returns the file being used for storing the output

getFileDescription() - Method in class weka.core.converters.AbstractFileSaver

to be pverridden

getFileDescription() - Method in class weka.core.converters.ArffLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.ArffSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.C45Loader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.C45Saver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.CSVLoader

getFileDescription() - Method in class weka.core.converters.CSVSaver

Returns a description of the file type.

getFileDescription() - Method in interface weka.core.converters.FileSourcedConverter

Get a one line description of the type of file

getFileDescription() - Method in class weka.core.converters.JSONLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.JSONSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.LibSVMLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.LibSVMSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.MatlabLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.MatlabSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SerializedInstancesLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SerializedInstancesSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SVMLightLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SVMLightSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.TextDirectoryLoader

Returns a description of the file type, actually it's directories.

getFileDescription() - Method in class weka.core.converters.XRFFLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.XRFFSaver

Returns a description of the file type.

getFileExtension() - Method in class weka.core.converters.AbstractFileSaver

Gets ihe file extension.

getFileExtension() - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

getFileExtension() - Method in class weka.core.converters.ArffLoader

Get the file extension used for arff files

getFileExtension() - Method in class weka.core.converters.C45Loader

Get the file extension used for arff files

getFileExtension() - Method in class weka.core.converters.CSVLoader

getFileExtension() - Method in interface weka.core.converters.FileSourcedConverter

Get the file extension used for this type of file

getFileExtension() - Method in class weka.core.converters.JSONLoader

Get the file extension used for JSON files.

getFileExtension() - Method in class weka.core.converters.LibSVMLoader

Get the file extension used for libsvm files.

getFileExtension() - Method in class weka.core.converters.MatlabLoader

Get the file extension used for libsvm files.

getFileExtension() - Method in interface weka.core.converters.Saver

Gets the file extension

getFileExtension() - Method in class weka.core.converters.SerializedInstancesLoader

Get the file extension used for arff files

getFileExtension() - Method in class weka.core.converters.SVMLightLoader

Get the file extension used for svm light files.

getFileExtension() - Method in class weka.core.converters.XRFFLoader

Get the file extension used for libsvm files

getFileExtensions() - Method in class weka.core.converters.AbstractFileSaver

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.ArffLoader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.ArffSaver

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.C45Loader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.CSVLoader

getFileExtensions() - Method in interface weka.core.converters.FileSourcedConverter

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.JSONLoader

Gets all the file extensions used for this type of file.

getFileExtensions() - Method in class weka.core.converters.JSONSaver

Gets all the file extensions used for this type of file.

getFileExtensions() - Method in class weka.core.converters.LibSVMLoader

Gets all the file extensions used for this type of file.

getFileExtensions() - Method in class weka.core.converters.MatlabLoader

Gets all the file extensions used for this type of file.

getFileExtensions() - Method in class weka.core.converters.SerializedInstancesLoader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.SVMLightLoader

Gets all the file extensions used for this type of file.

getFileExtensions() - Method in class weka.core.converters.XRFFLoader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.XRFFSaver

Gets all the file extensions used for this type of file

getFileFormat() - Method in class weka.gui.beans.SerializedModelSaver

Get the file format to use for saving.

getFileLoaders() - Static method in class weka.core.converters.ConverterUtils

returns a vector with the classnames of all the file loaders.

getFileMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns all the file/dir matches with the partial search string.

getFileMustExist() - Method in class weka.gui.ConverterFileChooser

Returns whether the selected file must exist (only open dialog).

getFileName() - Method in class weka.classifiers.bayes.net.BIFReader

returns the current filename

getFilename() - Method in class weka.core.Debug.Log

returns the filename of the log, can be null

getFilename() - Method in class weka.core.Debug.SimpleLog

returns the filename of the log, can be null

getFilename() - Method in class weka.core.FindWithCapabilities

returns the current filename for the dataset to base the capabilities on.

getFilename() - Method in class weka.gui.arffviewer.ArffPanel

returns the filename

getFilename(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the filename of the specified panel

getFilename() - Method in class weka.gui.beans.ImageSaver

Get the filename to save to

getFilename() - Method in class weka.gui.beans.TextSaver

Get the filename to save to

getFilename() - Method in class weka.gui.scripting.Script

Returns the current filename.

getFileSavers() - Static method in class weka.core.converters.ConverterUtils

returns a vector with the classnames of all the file savers.

getFillWithMissing() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).

getFilter() - Method in class weka.associations.FilteredAssociator

Gets the filter used.

getFilter() - Method in class weka.classifiers.meta.FilteredClassifier

Gets the filter used.

getFilter() - Method in class weka.clusterers.FilteredClusterer

Gets the filter used.

getFilter() - Method in class weka.filters.CheckSource

Gets the filter being used for the tests, can be null.

getFilter(int) - Method in class weka.filters.MultiFilter

Gets a single filter from the set of available filters.

getFilter(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets a single filter from the set of available filters.

getFilter() - Method in class weka.gui.beans.Filter

getFilter() - Method in class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent

returns the associated Capabilities filter

getFilter() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the default filter (fully configured) for the preprocess panel.

getFilterAfterFirstBatch() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.

getFiltered(int) - Method in class weka.classifiers.rules.RuleStats

Get the data after filtering the given rule

getFilteredInputFormat() - Method in class weka.attributeSelection.PrincipalComponents

Return the header of the training data after all filtering - i.e missing values and nominal to binary.

getFilters() - Method in class weka.filters.MultiFilter

Gets the list of possible filters to choose from.

getFilters() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets the list of possible filters to choose from.

getFilters() - Method in class weka.gui.scripting.GroovyScript

Returns the extension filters for this type of script.

getFilters() - Method in class weka.gui.scripting.JythonScript

Returns the extension filters for this type of script.

getFilters() - Method in class weka.gui.scripting.Script

Returns the extension filters for this type of script.

getFilterType() - Method in class weka.classifiers.functions.GaussianProcesses

Gets how the training data will be transformed.

getFilterType() - Method in class weka.classifiers.functions.SMO

Gets how the training data will be transformed.

getFilterType() - Method in class weka.classifiers.functions.SMOreg

Gets how the training data will be transformed.

getFind() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the current regular expression for .

getFindAllRulesForSupportLevel() - Method in class weka.associations.FPGrowth

Get whether all rules meeting the lower bound on min support and the minimum metric threshold are to be found.

getFindNumBins() - Method in class weka.filters.unsupervised.attribute.Discretize

Get the value of FindNumBins.

getFindNumBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Get the value of FindNumBins.

getFirstToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils

Gets token, skipping empty lines.

getFirstToken(StreamTokenizer) - Static method in class weka.core.converters.StreamTokenizerUtils

Gets token, skipping empty lines.

getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Get the index of the first value used.

getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues

Get the index of the first value used.

getFlag(char, String[]) - Static method in class weka.core.Utils

Checks if the given array contains the flag "-Char".

getFlag(String, String[]) - Static method in class weka.core.Utils

Checks if the given array contains the flag "-String".

getFlow() - Method in class weka.gui.beans.KnowledgeFlowApp

Gets the current flow being edited.

getFlowFile() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getFlowFile(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getFlows() - Method in class weka.gui.beans.FlowRunner

Get the vector holding the flow(s)

getFlowXML() - Method in class weka.gui.beans.KnowledgeFlowApp

Returns the current flow being edited in XML format.

getFMeasure() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the F-Measure.

getFold() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets the fold which is selected.

getFold() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets the fold which is selected.

getFoldColumn() - Method in class weka.experiment.PairedTTester

Get the value of FoldColumn.

getFoldColumn() - Method in interface weka.experiment.Tester

Get the value of FoldColumn.

getFolds() - Method in class weka.attributeSelection.OneRAttributeEval

Get the number of folds used for cross validation

getFolds() - Method in class weka.attributeSelection.WrapperSubsetEval

Get the number of folds used for accuracy estimation

getFolds() - Method in class weka.classifiers.rules.JRip

Gets the number of folds

getFolds() - Method in class weka.gui.beans.CrossValidationFoldMaker

Get the currently set number of folds

getFolds() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the number of folds used for cross-validation.

getFont() - Method in class weka.gui.visualize.PostscriptGraphics

Get current font.

getFontMetrics(Font) - Method in class weka.gui.visualize.PostscriptGraphics

Get Font metrics

getFontName() - Method in class weka.gui.scripting.SyntaxDocument

gets the current font family.

getFontRenderContext() - Method in class weka.gui.visualize.PostscriptGraphics

START overridden Graphics2D methods

getFontSize() - Method in class weka.gui.scripting.SyntaxDocument

gets the current font size.

getFontSizeAdjust() - Method in class weka.gui.beans.Note

Get the font size adjustment

getFormat() - Method in class weka.core.Debug.Timestamp

returns the current timestamp format

getFrameLocation() - Method in class weka.gui.MemoryUsagePanel

Returns the default position for the dialog.

getFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the title (incl.

getFrequency() - Method in class weka.associations.Item

Get the frequency of this item.

getFreshCardinalityOfParents(Instances) - Method in class weka.classifiers.bayes.net.ParentSet

returns cardinality of parents after recalculation

getFrom() - Method in class weka.core.pmml.jaxbbindings.Con1

Gets the value of the from property.

getFromYear() - Static method in class weka.core.Copyright

returns the start year of the copyright

getFStatistic() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the fStatistic property.

getFStatistic() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the fStatistic property.

getFunction(String) - Static method in class weka.core.pmml.Function

Get a built-in PMML Function.

getFunction(String, TransformationDictionary) - Static method in class weka.core.pmml.Function

Get either a function.

getFunction() - Method in class weka.core.pmml.jaxbbindings.Aggregate

Gets the value of the function property.

getFunction() - Method in class weka.core.pmml.jaxbbindings.Apply

Gets the value of the function property.

getFunction() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Gets the function for generating the data.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.MiningModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the value of the functionName property.

getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the functionName property.

getFValue() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the fValue property.

getGamma() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Gets the gamma value.

getGamma() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Gets the value of the gamma property.

getGamma() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType

Gets the value of the gamma property.

getGamma() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Gets the value of the gamma property.

getGamma() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Gets the value of the gamma property.

getGap() - Method in class weka.core.pmml.jaxbbindings.Delimiter

Gets the value of the gap property.

getGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate

Gets the value of the gaussianDistribution property.

getGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the gaussianDistribution property.

getGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the number of visible groups of siblings there are.

getGeneralRegressionModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the generalRegressionModel property.

getGenerateRanking() - Method in class weka.attributeSelection.GreedyStepwise

Gets whether ranking has been requested.

getGenerateRanking() - Method in interface weka.attributeSelection.RankedOutputSearch

Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search

getGenerateRanking() - Method in class weka.attributeSelection.Ranker

This is a dummy method.

getGenerateSparseData() - Method in class weka.gui.sql.SqlViewerDialog

Returns whether sparse data is generated.

getGenerator() - Method in class weka.gui.explorer.DataGeneratorPanel

returns the currently selected DataGenerator

getGeneratorSamplesBase() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Get the base used for computing the number of samples to obtain from each generator

getGlobalBlend() - Method in class weka.classifiers.lazy.KStar

Get the value of the global blend parameter

getGlobalInfo(Object, boolean) - Static method in class weka.core.Utils

Utility method for grabbing the global info help (if it exists) from an arbitrary object.

getGlobalInfo(Object) - Static method in class weka.gui.beans.KnowledgeFlowApp

Utility method for grabbing the global info help (if it exists) from an arbitrary object

getGlobalInputProperties() - Static method in class weka.gui.GenericPropertiesCreator

Get the global input properties

getGlobalModel() - Method in class weka.classifiers.trees.j48.NBTreeSplit

Return the global naive bayes model for this node

getGlobalOutputProperties() - Static method in class weka.gui.GenericPropertiesCreator

Get the global output properties

getGlobalTermWeights() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Gets the value of the globalTermWeights property.

getGracePeriod() - Method in class weka.classifiers.trees.HoeffdingTree

Get the number of instances (or total weight of instances) a leaf should observe between split attempts

getGraphString() - Method in class weka.gui.beans.GraphEvent

Return the dot string for the graph

getGraphTitle() - Method in class weka.gui.beans.GraphEvent

Return the graph title

getGraphType() - Method in class weka.gui.beans.GraphEvent

Return the graph type

getGridWidth() - Method in class weka.gui.beans.AttributeSummarizer

Get the width of the grid of plots

getGroupField() - Method in class weka.core.pmml.jaxbbindings.Aggregate

Gets the value of the groupField property.

getGroupIdentifier() - Method in class weka.gui.beans.BatchClassifierEvent

getGUI() - Method in class weka.classifiers.functions.MultilayerPerceptron

getGUIType() - Method in class weka.gui.Main

Gets the currently set type of GUI to display.

getH() - Method in class weka.core.matrix.QRDecomposition

Return the Householder vectors

getHandler() - Method in class weka.core.FindWithCapabilities

returns the current set CapabilitiesHandler to generate the dataset for, can be null.

getHandler() - Method in class weka.core.TestInstances

returns the current set CapabilitiesHandler to generate the dataset for, can be null

getHashtable(ArrayList<Object>, int) - Static method in class weka.associations.ItemSet

Return a hashtable filled with the given item sets.

getHashtable(ArrayList<Object>, int) - Static method in class weka.associations.LabeledItemSet

Return a hashtable filled with the given item sets.

getHeader() - Method in class weka.classifiers.evaluation.Evaluation

Returns the header of the underlying dataset.

getHeader() - Method in class weka.classifiers.Evaluation

Returns the header of the underlying dataset.

getHeader() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the header of the dataset.

getHeader() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the header property.

getHeader(String) - Method in class weka.experiment.ResultMatrix

returns the value associated with the given key, null if if cannot be found.

getHeight() - Method in class weka.gui.beans.BeanInstance

Gets the height of this bean

getHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the number of visible levels there are.

getHeuristicStop() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of heuristicStop.

getHiddenLayers() - Method in class weka.classifiers.functions.MultilayerPerceptron

getHighValue() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the highValue property.

getHistory() - Method in class weka.gui.GenericObjectEditor

Returns the history of the used setups.

getHistory() - Method in class weka.gui.GenericObjectEditorHistory

Returns the current history.

getHistory() - Method in class weka.gui.sql.ConnectionPanel

returns the history.

getHistory() - Method in class weka.gui.sql.event.HistoryChangedEvent

returns the history model

getHistory() - Method in class weka.gui.sql.QueryPanel

returns the history.

getHistoryItem() - Method in class weka.gui.GenericObjectEditorHistory.HistorySelectionEvent

Returns the selected history item.

getHistoryName() - Method in class weka.gui.sql.event.HistoryChangedEvent

returns the name of the history

getHoeffdingTieThreshold() - Method in class weka.classifiers.trees.HoeffdingTree

Get the threshold below which a split will be forced to break ties

getHomeDir() - Static method in class weka.core.Debug

returns the home directory of the user

getIcon() - Method in class weka.gui.scripting.GroovyPanel

Returns an icon to be used in a frame.

getIcon() - Method in class weka.gui.scripting.JythonPanel

Returns an icon to be used in a frame.

getIcon() - Method in class weka.gui.scripting.ScriptingPanel

Returns an icon to be used in a frame.

getIcon() - Method in class weka.gui.SimpleCLIPanel

Returns an icon to be used in a frame.

getIconPath() - Method in class weka.gui.beans.BeanVisual

returns the path for the icon

getId() - Method in class weka.classifiers.functions.neural.NeuralConnection

getID() - Method in class weka.core.Debug.Random

returns the unique ID of this number generator

getId() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Item

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Itemset

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.NeuralInput

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Node

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.TextDocument

Gets the value of the id property.

getId() - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Gets the value of the id property.

getID() - Method in class weka.core.pmml.VectorInstance

Get the ID of this vector instance

getID() - Method in class weka.core.Tag

Gets the numeric ID of the Tag.

getID() - Method in class weka.core.TechnicalInformation

returns the unique ID (either the one used in creating this instance or the automatically generated one)

getID() - Method in class weka.gui.streams.InstanceEvent

Get the event type

getID() - Method in class weka.gui.treevisualizer.TreeDisplayEvent

getIDFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.

getIDIndex() - Method in class weka.filters.unsupervised.attribute.AddID

Get the index of the attribute used.

getIDStr() - Method in class weka.core.Tag

Gets the string ID of the Tag.

getIgnoreCase() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

getIgnoreCase() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Get whether to ignore case when matching

getIgnoreCase() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Get whether to ignore case when matching

getIgnoreCaseForNames() - Method in class weka.classifiers.misc.InputMappedClassifier

Get whether to ignore case when matching attribute names and nominal values.

getIgnoreClass() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Gets the IgnoreClass value.

getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AddCluster

Gets ranges of attributes to be ignored.

getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Gets ranges of attributes to be ignored.

getIgnoredProperties() - Method in class weka.core.CheckGOE

Get the ignored properties used in checkToolTips() as comma-separated list (sorted).

getIgnoreRange() - Method in class weka.filters.unsupervised.attribute.MathExpression

Get the current range selection.

getImage() - Method in class weka.gui.beans.ImageEvent

Get the encapsulated image

getImage(String, String) - Static method in class weka.gui.ComponentHelper

returns the Image for a given directory and filename, NULL if not successful

getImage(String) - Static method in class weka.gui.ComponentHelper

returns the Image for a given filename, NULL if not successful

getImageIcon(String, String) - Static method in class weka.gui.ComponentHelper

returns the ImageIcon for a given filename and directory, NULL if not successful

getImageIcon(String) - Static method in class weka.gui.ComponentHelper

returns the ImageIcon for a given filename, NULL if not successful

getImagEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition

Return the imaginary parts of the eigenvalues

getImageName() - Method in class weka.gui.beans.ImageEvent

Get the name of the image

getImportance() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the importance property.

getImportance() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the importance property.

getIncludeClass() - Method in class weka.core.InstanceComparator

Returns whether the class is included in the comparison.

getIncludeClass() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Gets whether the class is included in the cleaning process or always skipped.

getIncludeRelationName() - Method in class weka.gui.beans.SerializedModelSaver

Get whether the relation name of the training data used to create the model is to be included in the filename of the serialized model.

getIndentationSize() - Method in class weka.gui.scripting.SyntaxDocument

Returns the number of blanks used for indentation.

getIndex() - Method in class weka.core.pmml.jaxbbindings.TimeValue

Gets the value of the index property.

getIndex() - Method in class weka.core.PropertyPath.PathElement

returns the index of the property, -1 if the property is not an index-based one

getIndex() - Method in class weka.core.SingleIndex

Gets the selected index.

getIndex() - Method in class weka.gui.SortedTableModel.SortContainer

Returns the original index of the item.

getIndices() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Gets the value of the indices property.

getIndices() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Gets the value of the indices property.

getInfoData() - Method in interface weka.gui.visualize.InstanceInfo

Returns the underlying data.

getInfoData() - Method in class weka.gui.visualize.InstanceInfoFrame

Returns the underlying data.

getInfoText() - Method in interface weka.gui.visualize.InstanceInfo

Returns the currently displayed info text.

getInfoText() - Method in class weka.gui.visualize.InstanceInfoFrame

Returns the currently displayed info text.

getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Gets whether to init as naive bayes

getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.K2

Gets whether to init as naive bayes

getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Gets whether to init as naive bayes

getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.K2

Gets whether to init as naive bayes

getInitFile() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the file to initialize the filter with, can be null.

getInitFileClassIndex() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the class index of the file to initialize the filter with.

getInitGenericObjectEditorFilter() - Static method in class weka.gui.explorer.ExplorerDefaults

returns if the GOEs in the Explorer will be initialized based on the data that is loaded into the Explorer.

getInitial() - Method in class weka.core.Memory

returns the initial size of the JVM heap, obtains a fresh MemoryUsage object to do so.

getInitialCount() - Method in class weka.classifiers.trees.REPTree

Get the value of InitialCount.

getInitialDatasetsDirectory() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the initial directory for the datasets (if empty, it returns the user's home directory).

getInitialDirectory() - Static method in class weka.gui.explorer.ExplorerDefaults

Returns the initial directory for the file chooser used for opening datasets.

getInitializationMethod() - Method in class weka.clusterers.SimpleKMeans

Get the initialization method to use

getInitialScore() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the initialScore property.

getInlineTable() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the inlineTable property.

getInlineTable() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the inlineTable property.

getInlineTable() - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Gets the value of the inlineTable property.

getInlineTable() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the inlineTable property.

getInputFilename() - Method in class weka.gui.GenericPropertiesCreator

returns the name of the input file

getInputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection

Use this to get easy access to the input numbers.

getInputOrder() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the input order.

getInputProperties() - Method in class weka.gui.GenericPropertiesCreator

returns the input properties object (template containing the packages)

getInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

Use this to get easy access to the inputs.

getInputs() - Method in class weka.gui.beans.MetaBean

getInputStream(String, String) - Static method in class weka.gui.Loader

returns an InputStream for the given dir and filename, can be NULL if it fails

getInputStream(String) - Method in class weka.gui.Loader

returns an InputStream for the given filename, can be NULL if it fails

getInputStructure() - Method in class weka.gui.beans.SubstringLabelerRules

Get the input structure

getInsertDummyNominalFirstValue() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Get whether a dummy first value will be inserted in the definition of each nominal attribute.

getInstalledLookAndFeels() - Static method in class weka.gui.LookAndFeel

returns an array with the classnames of all the installed LnFs

getInstalledPackageInfo(String) - Static method in class weka.core.WekaPackageManager

Get meta data for an installed package

getInstalledPackages() - Static method in class weka.core.WekaPackageManager

Get a list of installed packages

getInstance() - Method in class weka.gui.beans.InstanceEvent

Get the instance

getInstanceField() - Method in class weka.core.pmml.jaxbbindings.InstanceFields

Gets the value of the instanceField property.

getInstanceFields() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the instanceFields property.

getInstanceIdVariable() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the instanceIdVariable property.

getInstanceRange() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Gets the number of instances forward to translate values between.

getInstances() - Method in class weka.core.converters.AbstractSaver

Gets instances that should be stored.

getInstances() - Method in interface weka.core.DistanceFunction

returns the instances currently set.

getInstances() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

returns the instances currently set.

getInstances() - Method in class weka.core.NormalizableDistance

returns the instances currently set.

getInstances() - Method in class weka.core.xml.XMLInstances

returns the current instances, either the ones that were set or the ones that were generated from the XML structure.

getInstances() - Method in class weka.experiment.PairedTTester

Get the value of Instances.

getInstances() - Method in interface weka.experiment.Tester

Get the value of Instances.

getInstances() - Method in class weka.gui.arffviewer.ArffPanel

returns the instances of the panel, if none then NULL

getInstances() - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the data

getInstances() - Method in class weka.gui.arffviewer.ArffTableModel

returns the data

getInstances() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Get the training instances

getInstances() - Method in class weka.gui.explorer.AbstractPlotInstances

Returns the training data.

getInstances() - Method in class weka.gui.explorer.DataGeneratorPanel

returns the generated instances, null if the process was cancelled.

getInstances() - Method in class weka.gui.explorer.PreprocessPanel

Gets the working set of instances.

getInstances() - Method in class weka.gui.SetInstancesPanel

Gets the set of instances currently held by the panel.

getInstances() - Method in class weka.gui.treevisualizer.Node

This will return the Instances object related to this node.

getInstances() - Method in class weka.gui.ViewerDialog

returns the currently displayed instances

getInstances() - Method in class weka.gui.visualize.VisualizePanel

Get the master plot's instances

getInstances1() - Method in class weka.gui.visualize.VisualizePanelEvent

getInstances2() - Method in class weka.gui.visualize.VisualizePanelEvent

getInstancesFromClass(Instances, int, int, double, Instances) - Static method in class weka.estimators.EstimatorUtils

Returns a dataset that contains all instances of a certain class value.

getInstancesFromClass(Instances, int, double) - Static method in class weka.estimators.EstimatorUtils

Returns a dataset that contains of all instances of a certain class value.

getInstancesFromValue(Instances, int, double) - Static method in class weka.estimators.EstimatorUtils

Returns a dataset that contains of all instances of a certain value for the given attribute.

getInstancesIndices() - Method in class weka.filters.unsupervised.instance.RemoveRange

Gets ranges of instances selected.

getInstancesNoClass() - Method in class weka.associations.Apriori

Gets the instances without the class atrribute.

getInstancesNoClass() - Method in interface weka.associations.CARuleMiner

Gets the instances without the class attribute

getInstancesOnlyClass() - Method in class weka.associations.Apriori

Gets only the class attribute of the instances.

getInstancesOnlyClass() - Method in interface weka.associations.CARuleMiner

Gets the class attribute and its values for all instances

getInstancesValueAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the double value of the underlying Instances object at the given position, -1 if out of bounds

getInstancesValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the double value of the underlying Instances object at the given position, -1 if out of bounds

getINTEntries() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Gets the value of the intEntries property.

getIntercept() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns the intercept of the function.

getIntercept() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression

Returns the intercept of the function.

getIntercept() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the intercept property.

getInternalCacheSize() - Method in class weka.classifiers.functions.supportVector.StringKernel

Gets the size of the internal cache

getInterpolationMethod() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the interpolationMethod property.

getInterpreter() - Method in class weka.core.scripting.Jython

returns the currently used Python Interpreter

getInterQuartileRange() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the interQuartileRange property.

getInterval() - Method in class weka.core.pmml.jaxbbindings.ContStats

Gets the value of the interval property.

getInterval() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the interval property.

getInterval() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin

Gets the value of the interval property.

getInterval() - Method in class weka.core.pmml.jaxbbindings.EventValues

Gets the value of the interval property.

getInvalidFreq() - Method in class weka.core.pmml.jaxbbindings.Counts

Gets the value of the invalidFreq property.

getInvalidValueTreatment() - Method in class weka.core.pmml.jaxbbindings.Apply

Gets the value of the invalidValueTreatment property.

getInvalidValueTreatment() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the invalidValueTreatment property.

getInvert() - Method in class weka.core.InstanceComparator

Returns whether the matching sense of the attribute range is inverted.

getInvert() - Method in class weka.core.Range

Gets whether the range sense is inverted, i.e.

getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Get whether selection is inverted.

getInvertSelection() - Method in interface weka.core.DistanceFunction

Gets whether the matching sense of attribute indices is inverted or not.

getInvertSelection() - Method in class weka.core.NormalizableDistance

Gets whether the matching sense of attribute indices is inverted or not.

getInvertSelection() - Method in class weka.filters.supervised.attribute.Discretize

Gets whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Get whether the supplied attributes are to be acted on or all other attributes.

getInvertSelection() - Method in class weka.filters.supervised.instance.Resample

Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).

getInvertSelection() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets if selection is to be inverted.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Copy

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.MathExpression

Get whether the supplied columns are to be select or unselect

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Get whether the supplied attributes are to be acted on or all other attributes.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Gets whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Gets whether the selection of the columns is inverted

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Gets whether the supplied columns are to be worked on or the others.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Get whether the supplied columns are to be transformed or not

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Remove

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Get whether the supplied columns are to be removed or kept.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RemoveType

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Gets whether to invert the selection of the attributes.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.SortLabels

Gets whether the supplied columns are to be processed or skipped.

getInvertSelection() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether the supplied columns are to be processed or skipped.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets if selection is to be inverted.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Gets if selection is to be inverted.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveRange

Gets if selection is to be inverted.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Get whether the supplied columns are to be removed or kept

getInvertSelection() - Method in class weka.filters.unsupervised.instance.Resample

Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).

getIRClassValue() - Method in class weka.attributeSelection.WrapperSubsetEval

Get the class value (label or index) to use with IR metric evaluation of subsets.

getIsCenterField() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the isCenterField property.

getIsCyclic() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the isCyclic property.

getIsMultiValued() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the isMultiValued property.

getIsRecursive() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the isRecursive property.

getItemRef() - Method in class weka.core.pmml.jaxbbindings.ItemRef

Gets the value of the itemRef property.

getItemRef() - Method in class weka.core.pmml.jaxbbindings.Itemset

Gets the value of the itemRef property.

getItemValueAsString() - Method in class weka.associations.Item

Get this item's value as a String.

getItemValueAsString() - Method in class weka.associations.NominalItem

Get this item's value as a String.

getItemValueAsString() - Method in class weka.associations.NumericItem

Get this item's value as a String.

getIterativeClassifier() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Get the classifier used as the base learner.

getJaccard() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the jaccard property.

getJavaInitializationString() - Method in class weka.gui.beans.EnvironmentField

getJavaInitializationString() - Method in class weka.gui.CostMatrixEditor

Returns the Java code that generates an object the same as the one being edited.

getJavaInitializationString() - Method in class weka.gui.FileEditor

Returns a representation of the current property value as java source.

getJavaInitializationString() - Method in class weka.gui.GenericArrayEditor

Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.

getJavaInitializationString() - Method in class weka.gui.GenericObjectEditor

Supposedly returns an initialization string to create a Object identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.

getJavaInitializationString() - Method in class weka.gui.SelectedTagEditor

Returns a description of the property value as java source.

getJavaInitializationString() - Method in class weka.gui.SimpleDateFormatEditor

Returns the Java code that generates an object the same as the one being edited.

getJTable() - Method in class weka.gui.JTableHelper

returns the JTable

getKernel() - Method in class weka.classifiers.functions.GaussianProcesses

Gets the kernel to use.

getKernel() - Method in class weka.classifiers.functions.SMO.BinarySMO

Returns the kernel to use

getKernel() - Method in class weka.classifiers.functions.SMO

Returns the kernel to use

getKernel() - Method in class weka.classifiers.functions.SMOreg

Returns the kernel to use

getKernel() - Method in class weka.classifiers.functions.supportVector.CheckKernel

Get the kernel being tested

getKernel() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the kernel to use.

getKernelBandwidth() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Get the kernel bandwidth

getKernelEvaluations() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

returns the number of kernel evaluations

getKernelFactorExpression() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the expression for the kernel.

getKernelMatrixFile() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Gets the file containing the kernel matrix.

getKey() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the key describing the current SplitEvaluator.

getKey() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the key describing the current SplitEvaluator.

getKey() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the key describing the current SplitEvaluator.

getKey() - Method in interface weka.experiment.SplitEvaluator

Gets the key describing the current SplitEvaluator.

getKeyFieldName() - Method in class weka.experiment.AveragingResultProducer

Get the value of KeyFieldName.

getKeyNames() - Method in class weka.experiment.AveragingResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the names of each of the key columns produced for a single run.

getKeyNames() - Method in class weka.experiment.CrossValidationResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.DatabaseResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the names of each of the key columns produced for a single run.

getKeyNames() - Method in class weka.experiment.ExplicitTestsetResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.LearningRateResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.RandomSplitResultProducer

Gets the names of each of the columns produced for a single run.

getKeyNames() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the names of each of the key columns produced for a single run.

getKeyNames() - Method in interface weka.experiment.ResultProducer

Gets the names of each of the key columns produced for a single run.

getKeyNames() - Method in interface weka.experiment.SplitEvaluator

Gets the names of each of the key columns produced for a single run.

getKeys() - Method in class weka.core.converters.DatabaseLoader

Gets the key columns' name

getKeySpec() - Method in class weka.gui.beans.Join

Get the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)

getKeyTypes() - Method in class weka.experiment.AveragingResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the data types of each of the key columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.CrossValidationResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.DatabaseResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the data types of each of the key columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.ExplicitTestsetResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.LearningRateResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.RandomSplitResultProducer

Gets the data types of each of the columns produced for a single run.

getKeyTypes() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the data types of each of the key columns produced for a single run.

getKeyTypes() - Method in interface weka.experiment.ResultProducer

Gets the data types of each of the key columns produced for a single run.

getKeyTypes() - Method in interface weka.experiment.SplitEvaluator

Gets the data types of each of the key columns produced for a single run.

getKeywordFormatting(String) - Method in class weka.gui.scripting.SyntaxDocument

Gets the formatting for a keyword.

getKeywords() - Method in class weka.experiment.DatabaseUtils

Returns the currently stored keywords (as comma-separated list).

getKeywordsMaskChar() - Method in class weka.experiment.DatabaseUtils

Returns the currently set mask character.

getKind() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the kind property.

getKind() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the kind property.

getKNN() - Method in class weka.classifiers.lazy.IBk

Gets the number of neighbours the learner will use.

getKNN() - Method in class weka.classifiers.lazy.LWL

Gets the number of neighbours used for kernel bandwidth setting.

getKNNInput() - Method in class weka.core.pmml.jaxbbindings.KNNInputs

Gets the value of the knnInput property.

getKohonenMap() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the kohonenMap property.

getKValue() - Method in class weka.classifiers.trees.RandomTree

Get the value of K.

getKWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated bias squared according to the Kohavi and Wolpert definition

getKWSigma() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated sigma according to the Kohavi and Wolpert definition

getKWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated variance according to the Kohavi and Wolpert definition

getL() - Method in class weka.core.matrix.CholeskyDecomposition

Return triangular factor.

getL() - Method in class weka.core.Matrix

Deprecated. Returns the L part of the matrix.

getL() - Method in class weka.core.matrix.LUDecomposition

Return lower triangular factor

getLabel() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Gets the value of the label property.

getLabel() - Method in class weka.core.pmml.jaxbbindings.Parameter

Gets the value of the label property.

getLabel() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Get the label for the new merged class.

getLabel() - Method in class weka.gui.beans.BatchClassifierEvent

Get the label for this event

getLabel() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Get the label to assign if this rule matches, or empty string if binary flag attribute is being created.

getLabel() - Method in class weka.gui.treevisualizer.Edge

Get the value of label.

getLabel() - Method in class weka.gui.treevisualizer.Node

Get the value of label.

getLabels() - Method in class weka.filters.unsupervised.attribute.AddValues

Get the comma-separated list of labels that are added.

getLambda() - Method in class weka.classifiers.functions.SGD

Get the current value of lambda

getLambda() - Method in class weka.classifiers.functions.SGDText

Get the current value of lambda

getLambda() - Method in class weka.classifiers.functions.supportVector.StringKernel

Gets the lambda constant used in the string kernel

getLaunchCommand() - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin

Get the name of the launch command (to appear as the button text or in the popup menu)

getLaunchCommand() - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin

Get the name of the launch command (to appear as the button text or in the popup menu)

getLeafPredictionStrategy() - Method in class weka.classifiers.trees.HoeffdingTree

Get the leaf prediction strategy to use (majority class, naive Bayes or naive Bayes adaptive)

getLearningRate() - Method in class weka.classifiers.functions.MultilayerPerceptron

getLearningRate() - Method in class weka.classifiers.functions.SGD

Get the learning rate.

getLearningRate() - Method in class weka.classifiers.functions.SGDText

Get the learning rate.

getLeftMargin() - Method in class weka.core.pmml.jaxbbindings.Interval

Gets the value of the leftMargin property.

getLegendText() - Method in class weka.gui.beans.ChartEvent

Get the legend text vector

getLength() - Method in class weka.core.pmml.jaxbbindings.TextDocument

Gets the value of the length property.

getLength() - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Gets the value of the length property.

getLengthLimit() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the lengthLimit property.

getLevel() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the level property.

getLevel() - Method in class weka.gui.HierarchyPropertyParser

Get the level of current node.

getLeverage() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the leverage property.

getLift() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the lift property.

getLift() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the lift property.

getLiftData() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the liftData property.

getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph

Gets the value of the liftGraph property.

getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph

Gets the value of the liftGraph property.

getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph

Gets the value of the liftGraph property.

getLikelihoodThreshold() - Method in class weka.classifiers.meta.LogitBoost

Get the value of Precision.

getLine(int) - Method in class weka.gui.treevisualizer.Edge

Returns line number n

getLine(int) - Method in class weka.gui.treevisualizer.Node

Returns the text String for the specfied line.

getLinearNorm() - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Gets the value of the linearNorm property.

getLineNo() - Method in class weka.core.converters.ArffLoader.ArffReader

returns the current line number

getLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2

returns the element (Link) at a specific index from the list.

getLinkFunction() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the linkFunction property.

getLinkParameter() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the linkParameter property.

getLinkType() - Method in class weka.clusterers.HierarchicalClusterer

getList() - Method in class weka.gui.ResultHistoryPanel

Gets the JList used by the results list

getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.CheckBoxList.CheckBoxListRenderer

Return a component that has been configured to display the specified value.

getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer

Return a component that has been configured to display the specified value.

getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.sql.InfoPanelCellRenderer

Return a component that has been configured to display the specified value.

getLNorm() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get the L Norm used.

getLNorm() - Method in class weka.classifiers.functions.SGDText

Get the L Norm used.

getLoadClassifierFileName() - Method in class weka.gui.beans.Classifier

Get the name of the classifier to load at execution time.

getLoader() - Method in class weka.core.converters.ConverterUtils.DataSource

returns the determined loader, null if the DataSource was initialized with data alone and not a file/URL.

getLoader() - Method in class weka.gui.beans.Loader

Get the loader

getLoader() - Method in class weka.gui.ConverterFileChooser

returns the loader that was chosen by the user, can be null in case the user aborted the dialog or the save dialog was shown.

getLoader() - Method in class weka.gui.SetInstancesPanel

Gets the currently used Loader.

getLoaderForExtension(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the loader to use for this kind of extension, returns null if none can be found.

getLoaderForFile(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the loader to use for this kind of file, returns null if none can be found.

getLoaderForFile(File) - Static method in class weka.core.converters.ConverterUtils

tries to determine the loader to use for this kind of file, returns null if none can be found.

getLocallyPredictive() - Method in class weka.attributeSelection.CfsSubsetEval

Return true if including locally predictive attributes

getLocalTermWeights() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Gets the value of the localTermWeights property.

getLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the localTransformations property.

getLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the localTransformations property.

getLocator(int) - Method in class weka.core.AttributeLocator

Returns the AttributeLocator at the given index.

getLocatorIndices() - Method in class weka.core.AttributeLocator

Returns the indices of the AttributeLocator objects.

getLog() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get the logger.

getLog() - Method in class weka.core.Debug.Random

the currently used log, if null then stdout is used for outputting the debugging information

getLog() - Method in interface weka.core.LogHandler

Get the log in use

getLog() - Method in interface weka.core.pmml.PMMLModel

Get the logger.

getLogLikelihood() - Method in class weka.clusterers.ClusterEvaluation

Return the log likelihood corresponding to the most recent set of instances clustered.

getLogPanel(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getLookupCacheSize() - Method in class weka.attributeSelection.BestFirst

Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.

getLossFunction() - Method in class weka.classifiers.functions.SGD

Get the current loss function.

getLossFunction() - Method in class weka.classifiers.functions.SGDText

Get the current loss function.

getLower() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution

Gets the value of the lower property.

getLower() - Method in class weka.gui.experiment.RunNumberPanel

Gets the current lower run number.

getLowerBoundMinSupport() - Method in class weka.associations.Apriori

Get the value of lowerBoundMinSupport.

getLowerBoundMinSupport() - Method in class weka.associations.FPGrowth

Get the value of lowerBoundMinSupport.

getLowercaseTokens() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get whether to convert all tokens to lowercase

getLowercaseTokens() - Method in class weka.classifiers.functions.SGDText

Get whether to convert all tokens to lowercase

getLowerCaseTokens() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether if the tokens are to be downcased or not.

getLowerNumericBound() - Method in class weka.core.Attribute

Returns the lower bound of a numeric attribute.

getLowerSize() - Method in class weka.experiment.LearningRateResultProducer

Get the value of LowerSize.

getLowValue() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the lowValue property.

getM5RootNode() - Method in class weka.classifiers.trees.m5.M5Base

getM5RootNode() - Method in class weka.classifiers.trees.m5.Rule

getMainPanel() - Method in class weka.gui.arffviewer.ArffViewer

returns the main panel

getMainPerspective() - Method in class weka.gui.beans.KnowledgeFlowApp

Gets the main knowledge flow perspective

getMakeBinary() - Method in class weka.filters.supervised.attribute.Discretize

Gets whether binary attributes should be made for discretized ones.

getMakeBinary() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets whether binary attributes should be made for discretized ones.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.Apply

Gets the value of the mapMissingTo property.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.Discretize

Gets the value of the mapMissingTo property.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.FieldRef

Gets the value of the mapMissingTo property.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the mapMissingTo property.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Gets the value of the mapMissingTo property.

getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Gets the value of the mapMissingTo property.

getMappedClassIndex() - Method in class weka.classifiers.misc.InputMappedClassifier

getMappedValue() - Method in class weka.core.pmml.jaxbbindings.Item

Gets the value of the mappedValue property.

getMapValues() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the mapValues property.

getMapValues() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the mapValues property.

getMapValues() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the mapValues property.

getMargin(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

return marginal distibution for a node

getMargin(int) - Method in class weka.classifiers.bayes.net.MarginCalculator

getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

getMasterPlot() - Method in class weka.gui.visualize.Plot2D

Get the master plot

getMatCell() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the matCell property.

getMatch() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Get the string/regex to use for matching

getMatch() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Get the string/regex to use for matching

getMatchAttributeName() - Method in class weka.gui.beans.SubstringLabeler

getMatchDetails() - Method in class weka.gui.beans.SubstringLabeler

Get the internally encoded list of match rules

getMatches() - Method in class weka.core.FindWithCapabilities

returns the matches from the last find call.

getMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns all the matches with the partial search string, files or classes.

getMatchMissingValues() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Gets whether missing values are counted as a match.

getMatchReplaceDetails() - Method in class weka.gui.beans.SubstringReplacer

Get the internally encoded list of match-replace rules

getMatrix(int, int, int, int) - Method in class weka.core.matrix.Matrix

Get a submatrix.

getMatrix(int[], int[]) - Method in class weka.core.matrix.Matrix

Get a submatrix.

getMatrix(int, int, int[]) - Method in class weka.core.matrix.Matrix

Get a submatrix.

getMatrix(int[], int, int) - Method in class weka.core.matrix.Matrix

Get a submatrix.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.Comparisons

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.CorrelationValues

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.Covariances

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix

Gets the value of the matrix property.

getMatrix() - Method in class weka.core.pmml.jaxbbindings.Predictor

Gets the value of the matrix property.

getMax() - Method in class weka.core.Memory

returns the maximum size of the JVM heap, obtains a fresh MemoryUsage object to do so.

getMax() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the max property.

getMax() - Method in class weka.core.pmml.jaxbbindings.Time

Gets the value of the max property.

getMax() - Method in class weka.gui.beans.ChartEvent

Get the max y value

getMaxArray() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns the calculated maximum values for the attributes in the data.

getMaxBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of maxBoostingIterations.

getMaxC() - Method in class weka.gui.visualize.Plot2D

Return the current max value of the colouring attribute

getMaxCardinality() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

returns the max cardinality

getMaxCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the maximum of coords per point.

getMaxCost(int) - Method in class weka.classifiers.CostMatrix

Gets the maximum cost for a particular class value.

getMaxCost(int, Instance) - Method in class weka.classifiers.CostMatrix

Gets the maximum cost for a particular class value.

getMaxCount() - Method in class weka.filters.supervised.instance.SpreadSubsample

Gets the value for the max count

getMaxDecimalPlaces() - Method in class weka.core.converters.ArffSaver

Get the maximum number of decimal places to print

getMaxDecimalPlaces() - Method in class weka.core.converters.CSVSaver

Get the maximum number of decimal places to print

getMaxDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the maximum default.

getMaxDepth() - Method in class weka.classifiers.trees.RandomForest

Get the maximum depth of trh tree, 0 for unlimited.

getMaxDepth() - Method in class weka.classifiers.trees.RandomTree

Get the maximum depth of trh tree, 0 for unlimited.

getMaxDepth() - Method in class weka.classifiers.trees.REPTree

Get the value of MaxDepth.

getMaxDepth() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the depth of the built tree.

getMaximum() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the maximum property.

getMaximum() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the maximum property.

getMaximumAntConsSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumAntConsSeparationTime property.

getMaximumAttributeNames() - Method in class weka.attributeSelection.PrincipalComponents

Gets maximum number of attributes to include in transformed attribute names.

getMaximumAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Gets maximum number of attributes to include in transformed attribute names.

getMaximumAttributes() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Gets maximum number of PC attributes to retain.

getMaximumItemsetSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumItemsetSeparationTime property.

getMaximumNumberOfAntecedentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumNumberOfAntecedentItems property.

getMaximumNumberOfClusters() - Method in class weka.clusterers.EM

Get the maximum number of clusters to consider when cross-validating

getMaximumNumberOfConsequentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumNumberOfConsequentItems property.

getMaximumNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumNumberOfItems property.

getMaximumTotalSequenceTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the maximumTotalSequenceTime property.

getMaximumVariancePercentageAllowed() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Gets the maximum variance attributes are allowed to have before they are deleted by the filter.

getMaxInfoGain() - Method in class weka.classifiers.rules.JRip.Antd

getMaxInstancesInLeaf() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the maximum number of instances allowed in a leaf.

getMaxInstInLeaf() - Method in class weka.core.neighboursearch.KDTree

Get the maximum number of instances in a leaf.

getMaxInstNum() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the upper boundary for instances per cluster.

getMaxInstNum() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Gets the upper boundary for instances per cluster.

getMaxIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

returns the maximum of internal nodes visited.

getMaxIterations() - Method in class weka.classifiers.trees.lmt.LogisticBase

Returns the maxIterations parameter.

getMaxIterations() - Method in class weka.clusterers.EM

Get the maximum number of iterations

getMaxIterations() - Method in class weka.clusterers.SimpleKMeans

gets the number of maximum iterations to be executed.

getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the maximum number of cleansing iterations performed

getMaxIts() - Method in class weka.classifiers.functions.Logistic

Get the value of MaxIts.

getMaxK() - Method in class weka.classifiers.functions.VotedPerceptron

Get the value of maxK.

getMaxLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the maximum number of leaves visited.

getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Gets the max number of parents.

getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.K2

Gets the max number of parents.

getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Gets the max number of parents.

getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.K2

Gets the max number of parents.

getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Gets the max number of parents.

getMaxNumberOfItems() - Method in class weka.associations.FPGrowth

Gets the maximum number of items to be included in large item sets.

getMaxNumberOfItemsPerTA() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the maxNumberOfItemsPerTA property.

getMaxNumberOfItemsPerTransaction() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the maxNumberOfItemsPerTransaction property.

getMaxNumberOfTAsPerTAGroup() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the maxNumberOfTAsPerTAGroup property.

getMaxNumCandidateCanopiesToHoldInMemory() - Method in class weka.clusterers.Canopy

Get the maximum number of candidate canopies to retain in memory during training.

getMaxPlots() - Method in class weka.gui.beans.AttributeSummarizer

Get the number of plots to display

getMaxPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the maximum of points visited.

getMaxRadius() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the upper boundary for the radiuses of the clusters.

getMaxRange() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the upper boundary for the range of x

getMaxRelativeLeafRadius() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the maximum relative radius of a leaf node.

getMaxRows() - Method in class weka.gui.sql.event.QueryExecuteEvent

returns the maximum number of rows to retrieve.

getMaxRows() - Method in class weka.gui.sql.QueryPanel

returns the current value for the maximum number of rows.

getMaxRows() - Method in class weka.gui.sql.ResultSetHelper

the maximum number of rows to retrieve, less than 1 means unlimited.

getMaxRuleSize() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the maximum number of tests in rules.

getMaxRunNumber() - Method in class weka.gui.beans.BatchClassifierEvent

Get the maximum run number

getMaxRunNumber() - Method in class weka.gui.beans.TestSetEvent

Get the maximum number of runs.

getMaxRunNumber() - Method in class weka.gui.beans.TrainingSetEvent

Get the maximum number of runs.

getMaxSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent

Get the maximum set number (ie the total number of training and testing sets in the series).

getMaxSetNumber() - Method in class weka.gui.beans.BatchClustererEvent

Get the maximum set number (ie the total number of training and testing sets in the series).

getMaxSetNumber() - Method in class weka.gui.beans.TestSetEvent

Get the maximum set number

getMaxSetNumber() - Method in class weka.gui.beans.TrainingSetEvent

Get the maximum set number

getMaxSubsequenceLength() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the maximum length of the subsequence

getMaxThreshold() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the maximum threshold.

getMaxTime() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables

Gets the value of the maxTime property.

getMaxTime() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Gets the value of the maxTime property.

getMaxValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getMaxVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxX() - Method in class weka.gui.visualize.Plot2D

Return the current max value of the attribute plotted on the x axis

getMaxXBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).

getMaxY() - Method in class weka.gui.visualize.Plot2D

Return the current max value of the attribute plotted on the y axis

getMaxYBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).

getMean() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution

Gets the value of the mean property.

getMean() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution

Gets the value of the mean property.

getMean() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the mean property.

getMean() - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution

Gets the value of the mean property.

getMean() - Method in class weka.core.pmml.jaxbbindings.Time

Gets the value of the mean property.

getMean() - Method in class weka.estimators.MultivariateGaussianEstimator

getMean() - Method in class weka.estimators.NormalEstimator

Return the value of the mean of this normal estimator.

getMean(int, int) - Method in class weka.experiment.ResultMatrix

returns the mean at the given position, if the position is valid, otherwise 0.

getMeanAbsoluteError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the meanAbsoluteError property.

getMeanCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the mean of coords per point.

getMeanError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the meanError property.

getMeanIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the mean of internal nodes visited.

getMeanLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the mean of number of leaves visited.

getMeanOfSquares() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the meanOfSquares property.

getMeanPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the mean of points visited.

getMeanPrec() - Method in class weka.experiment.ResultMatrix

returns the current precision for the means.

getMeanPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default precision for the mean.

getMeans() - Method in class weka.estimators.KernelEstimator

Return the means of the kernels.

getMeanSquared() - Method in class weka.classifiers.lazy.IBk

Gets whether the mean squared error is used rather than mean absolute error when doing cross-validation.

getMeanSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the meanSquaredError property.

getMeanStddev() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

returns the current mean/stddev setup

getMeanValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getMeanWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the mean.

getMeasure(String) - Method in class weka.classifiers.bayes.BayesNet

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.functions.SimpleLogistic

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.functions.SMOreg

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.lazy.IBk

Returns the value of the named measure from the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.

getMeasure(String) - Method in class weka.classifiers.lazy.LWL

Returns the value of the named measure from the neighbour search algorithm.

getMeasure(String) - Method in class weka.classifiers.meta.AdditiveRegression

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.meta.Bagging

Returns the value of the named measure.

getMeasure(String) - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.rules.DecisionTable

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.rules.JRip

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.rules.PART

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.trees.J48

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.trees.LMT

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.trees.m5.M5Base

Returns the value of the named measure

getMeasure(String) - Method in class weka.classifiers.trees.RandomForest

Returns the value of the named measure.

getMeasure(String) - Method in class weka.classifiers.trees.REPTree

Returns the value of the named measure.

getMeasure(String) - Method in interface weka.core.AdditionalMeasureProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.core.neighboursearch.BallTree

Returns the value of the named measure.

getMeasure(String) - Method in class weka.core.neighboursearch.CoverTree

Returns the value of the named measure.

getMeasure(String) - Method in class weka.core.neighboursearch.KDTree

Returns the value of the named measure.

getMeasure(String) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns the value of the named measure.

getMeasure(String) - Method in class weka.core.neighboursearch.PerformanceStats

Returns the value of the named measure.

getMeasure(String) - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the value of the named measure.

getMeasure(String) - Method in class weka.experiment.AveragingResultProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.ClassifierSplitEvaluator

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.CrossValidationResultProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.DatabaseResultProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the value of the named measure.

getMeasure(String) - Method in class weka.experiment.LearningRateResultProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.RandomSplitResultProducer

Returns the value of the named measure

getMeasure(String) - Method in class weka.experiment.RegressionSplitEvaluator

Returns the value of the named measure

getMeasurePerformance() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Gets whether performance statistics are being calculated or not.

getMedian() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the median property.

getMembershipValues(Instance) - Method in class weka.classifiers.meta.Bagging

Computes an array that indicates leaf membership

getMembershipValues(Instance) - Method in class weka.classifiers.meta.FilteredClassifier

Computes an array that has a value for each element in the partition.

getMembershipValues(Instance) - Method in class weka.classifiers.meta.RandomCommittee

Computes an array that indicates leaf membership

getMembershipValues(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree

Computes a list that indicates node membership

getMembershipValues(Instance) - Method in class weka.classifiers.trees.J48

Computes an array that indicates node membership.

getMembershipValues(Instance) - Method in class weka.classifiers.trees.RandomForest

Computes an array that indicates leaf membership

getMembershipValues(Instance) - Method in class weka.classifiers.trees.RandomTree

Computes array that indicates node membership.

getMembershipValues(Instance) - Method in class weka.classifiers.trees.REPTree

Computes array that indicates node membership.

getMembershipValues(Instance) - Method in interface weka.core.PartitionGenerator

Computes an array that has a value for each element in the partition.

getMenu() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the menu bar to be added in a frame

getMenuBar() - Method in class weka.classifiers.bayes.net.GUI

Get the menu bar for this application.

getMenuBar() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin

Return the menu bar for this plugin

getMenuBar() - Method in class weka.gui.scripting.FileScriptingPanel

Returns the menu bar to to be displayed in the frame.

getMenuBar() - Method in class weka.gui.scripting.ScriptingPanel

Returns the menu bar to to be displayed in the frame.

getMenuBar() - Method in class weka.gui.SimpleCLIPanel

Not supported.

getMenuEntryText() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin

Get the text entry to appear in the menu

getMenuTitle() - Method in interface weka.gui.MainMenuExtension

Returns the name of the menu item.

getMenuToDisplayIn() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin

Get the menu that the plugin is to be listed in

getMergeValueRange() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Get the range of the merge values used.

getMetaClassifier() - Method in class weka.classifiers.meta.Stacking

Gets the meta classifier.

getMetadata() - Method in class weka.core.Attribute

Returns the properties supplied for this attribute.

getMetaData() - Method in class weka.core.converters.DatabaseConnection

Gets meta data for the database connection object.

getMethod() - Method in class weka.classifiers.functions.neural.NeuralNode

getMethod() - Method in class weka.classifiers.meta.MultiClassClassifier

Gets the method used.

getMethod() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Gets the value of the method property.

getMethodName() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Get the transformation method.

getMetricDescription() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Get a short description of this metric (algorithm, forumulas etc.).

getMetricName() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Get the name of this metric

getMetricNamesForRule() - Method in class weka.associations.AssociationRule

Return the names of the metrics available for this rule.

getMetricNamesForRule() - Method in class weka.associations.DefaultAssociationRule

getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.GiniSplitMetric

getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.InfoGainSplitMetric

getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.SplitMetric

Get the range of the splitting metric

getMetricsToDisplay() - Method in class weka.classifiers.evaluation.Evaluation

Get a list of the names of metrics to have appear in the output The default is to display all built in metrics and plugin metrics that haven't been globally disabled.

getMetricsToDisplay() - Method in class weka.classifiers.Evaluation

Get a list of the names of metrics to have appear in the output The default is to display all built in metrics and plugin metrics that haven't been globally disabled.

getMetricType() - Method in class weka.associations.Apriori

Get the metric type

getMetricType() - Method in class weka.associations.FPGrowth

Get the metric type to use.

getMetricValuesForRule() - Method in class weka.associations.AssociationRule

Get all the available metric values for this rule.

getMetricValuesForRule() - Method in class weka.associations.DefaultAssociationRule

getMiddle(double[]) - Method in class weka.core.EuclideanDistance

Returns value in the middle of the two parameter values.

getMin() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the min property.

getMin() - Method in class weka.core.pmml.jaxbbindings.Time

Gets the value of the min property.

getMin() - Method in class weka.gui.beans.ChartEvent

Get the min y value

getMinArray() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns the calculated minimum values for the attributes in the data.

getMinBoxRelWidth() - Method in class weka.core.neighboursearch.KDTree

Gets the minimum relative box width.

getMinBucketSize() - Method in class weka.classifiers.rules.OneR

Get the value of minBucketSize.

getMinC() - Method in class weka.gui.visualize.Plot2D

Return the current min value of the colouring attribute

getMinCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the minimum of coords per point.

getMinDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the minimum default.

getMinFunction() - Method in class weka.core.Optimization

Get the minimal function value

getMinimal() - Method in class weka.classifiers.functions.LinearRegression

Returns whether to be more memory conservative or being able to output the model as string.

getMinimizeAbsoluteError() - Method in class weka.classifiers.meta.RegressionByDiscretization

Gets whether to min.

getMinimizeExpectedCost() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Gets the value of MinimizeExpectedCost.

getMinimum() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the minimum property.

getMinimum() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the minimum property.

getMinimumAntConsSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumAntConsSeparationTime property.

getMinimumBucketSize() - Method in class weka.attributeSelection.OneRAttributeEval

Get the minimum bucket size used by oneR

getMinimumCanopyDensity() - Method in class weka.clusterers.Canopy

Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.

getMinimumConfidence() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the minimumConfidence property.

getMinimumConfidence() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumConfidence property.

getMinimumFractionOfWeightInfoGain() - Method in class weka.classifiers.trees.HoeffdingTree

Get the minimum fraction of weight required down at least two branches for info gain splitting

getMinimumFrequency() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Gets the minimum frequency.

getMinimumItemsetSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumItemsetSeparationTime property.

getMinimumLift() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumLift property.

getMinimumNumberInstances() - Method in class weka.core.Capabilities

returns the minimum number of instances that have to be in the dataset

getMinimumNumberOfAntecedentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumNumberOfAntecedentItems property.

getMinimumNumberOfConsequentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumNumberOfConsequentItems property.

getMinimumNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumNumberOfItems property.

getMinimumSupport() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the minimumSupport property.

getMinimumSupport() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumSupport property.

getMinimumTotalSequenceTime() - Method in class weka.core.pmml.jaxbbindings.Constraints

Gets the value of the minimumTotalSequenceTime property.

getMiningBuildTask() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the miningBuildTask property.

getMiningFields() - Method in class weka.core.pmml.jaxbbindings.MiningSchema

Gets the value of the miningField property.

getMiningFields() - Method in class weka.core.pmml.MiningSchema

getMiningModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the miningModel property.

getMiningSchema() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get the mining schema for this model.

getMiningSchema() - Method in interface weka.core.pmml.PMMLModel

Get the mining schema.

getMiningSchemaAsInstances() - Method in class weka.core.pmml.MiningSchema

Get the mining schema fields as an Instances object.

getMinInstNum() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the lower boundary for instances per cluster.

getMinInstNum() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Gets the lower boundary for instances per cluster.

getMinIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the minimum of internal nodes visited.

getMinkowski() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the minkowski property.

getMinLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the minimum number of leaves visited.

getMinLevel() - Method in class weka.core.logging.Logger

Returns the minimum level log messages must have in order to appear in the log.

getMinLogLikelihoodImprovementCV() - Method in class weka.clusterers.EM

Get the minimum improvement in cross-validated log likelihood required to consider increasing the number of clusters when cross-validating to find the best number of clusters

getMinLogLikelihoodImprovementIterating() - Method in class weka.clusterers.EM

Get the minimum improvement in log likelihood necessary to perform another iteration of the E and M steps.

getMinMax(Instances, int, double[]) - Static method in class weka.estimators.CheckEstimator

Find the minimum and the maximum of the attribute and return it in the last parameter..

getMinMax(Instances, int, double[]) - Static method in class weka.estimators.EstimatorUtils

Find the minimum and the maximum of the attribute and return it in the last parameter..

getMinMetric() - Method in class weka.associations.Apriori

Get the value of minConfidence.

getMinMetric() - Method in class weka.associations.FPGrowth

Get the value of minConfidence.

getMinNo() - Method in class weka.classifiers.rules.JRip

Gets the minimum total weight of the instances in a rule

getMinNum() - Method in class weka.classifiers.trees.RandomTree

Get the value of MinNum.

getMinNum() - Method in class weka.classifiers.trees.REPTree

Get the value of MinNum.

getMinNumInstances() - Method in class weka.classifiers.trees.LMT

Get the value of minNumInstances.

getMinNumInstances() - Method in class weka.classifiers.trees.m5.M5Base

Get the minimum number of instances to allow at a leaf node

getMinNumInstances() - Method in class weka.classifiers.trees.m5.Rule

Get the minimum number of instances to allow at a leaf node

getMinNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode

Get the minimum number of instances to allow at a leaf node

getMinNumObj() - Method in class weka.classifiers.rules.PART

Get the value of minNumObj.

getMinNumObj() - Method in class weka.classifiers.trees.J48

Get the value of minNumObj.

getMinPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the minimum of points visited.

getMinRadius() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the lower boundary for the radiuses of the clusters.

getMinRange() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the lower boundary for the range of x

getMinRuleSize() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the minimum number of tests in rules.

getMinStdDev() - Method in class weka.clusterers.EM

Get the minimum allowable standard deviation.

getMinStdDev() - Method in class weka.clusterers.MakeDensityBasedClusterer

Get the minimum allowable standard deviation.

getMinTermFreq() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Get the MinTermFreq value.

getMinThreshold() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Get the minimum threshold.

getMinValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getMinVarianceProp() - Method in class weka.classifiers.trees.RandomTree

Get the value of MinVarianceProp.

getMinVarianceProp() - Method in class weka.classifiers.trees.REPTree

Get the value of MinVarianceProp.

getMinVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinWordFrequency() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get the minimum word frequency.

getMinWordFrequency() - Method in class weka.classifiers.functions.SGDText

Get the minimum word frequency.

getMinX() - Method in class weka.gui.visualize.Plot2D

Return the current min value of the attribute plotted on the x axis

getMinXBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Gets the minimum x-coordinate bound, in training-instance units (not mouse coordinates).

getMinY() - Method in class weka.gui.visualize.Plot2D

Return the current min value of the attribute plotted on the y axis

getMinYBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Gets the minimum y-coordinate bound, in training-instance units (not mouse coordinates).

getMisses() - Method in class weka.core.FindWithCapabilities

returns the misses from the last find call.

getMissingFreq() - Method in class weka.core.pmml.jaxbbindings.Counts

Gets the value of the missingFreq property.

getMissingMerge() - Method in class weka.attributeSelection.GainRatioAttributeEval

get whether missing values are being distributed or not

getMissingMerge() - Method in class weka.attributeSelection.InfoGainAttributeEval

get whether missing values are being distributed or not

getMissingMerge() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

get whether missing values are being distributed or not

getMissingMode() - Method in class weka.classifiers.lazy.KStar

Gets the method to use for handling missing values.

getMissingSeparate() - Method in class weka.attributeSelection.CfsSubsetEval

Return true is missing is treated as a separate value

getMissingValue() - Method in class weka.core.converters.CSVLoader

Returns the current placeholder for missing values.

getMissingValue() - Method in class weka.core.converters.CSVSaver

Returns the current placeholder for missing values.

getMissingValuePenalty() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the missingValuePenalty property.

getMissingValuePenalty() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the missingValuePenalty property.

getMissingValueReplacement() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the missingValueReplacement property.

getMissingValueStrategy() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the missingValueStrategy property.

getMissingValueStrategy() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the missingValueStrategy property.

getMissingValueTreatment() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the missingValueTreatment property.

getMissingValueTreatmentMethod() - Method in class weka.core.pmml.MiningFieldMetaInfo

Get the missing value treatment method for this field.

getModalValue() - Method in class weka.core.pmml.jaxbbindings.DiscrStats

Gets the value of the modalValue property.

getModel() - Method in class weka.classifiers.trees.m5.RuleNode

Get the linear model at this node

getModel() - Method in class weka.gui.SortedTableModel

returns the current model, can be null

getModelClass() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the modelClass property.

getModelDF() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the modelDF property.

getModelFile() - Method in class weka.classifiers.misc.SerializedClassifier

Gets the file containing the serialized model.

getModelHeader(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier

Return the instance structure that the encapsulated model was built with.

getModelLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the modelLiftGraph property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.MiningModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the value of the modelName property.

getModelName() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the modelName property.

getModelParameters() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.

getModelPath() - Method in class weka.classifiers.misc.InputMappedClassifier

Get the path used for loading a model.

getModelStats() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the modelStats property.

getModelStats() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the modelStats property.

getModelType() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the modelType property.

getModelType() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the modelType property.

getModelValueAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the value at the given position

getModifyHeader() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Gets whether the header will be modified when selecting on nominal attributes.

getModifyHeader() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Gets whether the header will be modified when selecting on nominal attributes.

getMomentum() - Method in class weka.classifiers.functions.MultilayerPerceptron

getMultiInstance() - Method in class weka.core.TestInstances

Gets whether multi-instance data (with a fixed structure) is generated

getMultiInstanceCapabilities() - Method in interface weka.core.MultiInstanceCapabilitiesHandler

Returns the capabilities of this multi-instance classifier for the relational data (i.e., the bags).

getMultiLineComment() - Method in class weka.gui.scripting.SyntaxDocument

Returns whether multi-line comments are enabled.

getMultiLineCommentEnd() - Method in class weka.gui.scripting.SyntaxDocument

Returns the end of a multi-line comment.

getMultiLineCommentStart() - Method in class weka.gui.scripting.SyntaxDocument

Returns the string that is the start of a multi-line comment.

getMultipleModelMethod() - Method in class weka.core.pmml.jaxbbindings.Segmentation

Gets the value of the multipleModelMethod property.

getMultivariateStat() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats

Gets the value of the multivariateStat property.

getMultivariateStats() - Method in class weka.core.pmml.jaxbbindings.ModelStats

Gets the value of the multivariateStats property.

getN() - Method in class weka.core.pmml.jaxbbindings.ArrayType

Gets the value of the n property.

getN() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Gets the value of the n property.

getN() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Gets the value of the n property.

getNaiveBayesModel() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Get the naive bayes model at this node

getNaiveBayesModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the naiveBayesModel property.

getNaiveBayesPredictionThreshold() - Method in class weka.classifiers.trees.HoeffdingTree

Get the number of instances (weight) a leaf should observe before allowing naive Bayes to make predictions

getName() - Method in class weka.classifiers.bayes.BayesNet

get name of the Bayes network

getName() - Method in class weka.core.json.JSONNode

Returns the name of the node.

getName() - Method in class weka.core.pmml.Function

getName() - Method in class weka.core.pmml.jaxbbindings.Application

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Characteristic

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Extension

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Parameter

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.ParameterField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Partition

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Predictor

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.Taxonomy

Gets the value of the name property.

getName() - Method in class weka.core.pmml.jaxbbindings.TextDocument

Gets the value of the name property.

getName() - Method in class weka.core.pmml.MiningFieldMetaInfo

Get the name of this field.

getName() - Method in class weka.core.PropertyPath.PathElement

returns the name of the property

getName() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns the name of the new attribute

getName() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the name of the new attribute

getName() - Method in class weka.gui.visualize.VisualizePanel

Returns the name associated with this plot.

getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute(Instances, Attribute) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

Extracts the original attribute name and value from the name of a binary indicator attribute created by unsupervised NominalToBinary.

getNameAtIndex(int) - Method in class weka.gui.ResultHistoryPanel

Gets the name of theitem in the list at the specified index

getNamedBuffer(String) - Method in class weka.gui.ResultHistoryPanel

Gets the named buffer

getNamedMetric(String, int...) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper

Gets the value of a named metric.

getNamedMetricValue(String) - Method in class weka.associations.AssociationRule

Get the value of the named metric for this rule

getNamedMetricValue(String) - Method in class weka.associations.DefaultAssociationRule

getNamedObject(String) - Method in class weka.gui.ResultHistoryPanel

Get the named object from the list

getNbCols() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the nbCols property.

getNbCorrect() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the nbCorrect property.

getNbCorrect() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the nbCorrect property.

getNbRows() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the nbRows property.

getNearestNeighborModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the nearestNeighborModel property.

getNearestNeighbourSearchAlgorithm() - Method in class weka.classifiers.lazy.IBk

Returns the current nearestNeighbourSearch algorithm in use.

getNearestNeighbourSearchAlgorithm() - Method in class weka.classifiers.lazy.LWL

Returns the current nearestNeighbourSearch algorithm in use.

getNegativeTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the negativeTargetFieldDisplayValue property.

getNegativeTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the negativeTargetFieldValue property.

getNeuralInput() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs

Gets the value of the neuralInput property.

getNeuralNetwork() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the neuralNetwork property.

getNeuralOutput() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs

Gets the value of the neuralOutput property.

getNeuron() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the neuron property.

getNewAttributeName() - Method in class weka.gui.beans.SubstringLabelerRules

Get the name to use for the new attribute that is added

getNewLine() - Method in class weka.gui.scripting.Script

Returns the new line string in use.

getNext(int) - Method in class weka.classifiers.functions.supportVector.SMOset

Gets the next element in the set.

getNextInstance(Instances) - Method in class weka.core.converters.AbstractLoader

getNextInstance(Instances) - Method in class weka.core.converters.ArffLoader

Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.

getNextInstance(Instances) - Method in class weka.core.converters.C45Loader

Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.

getNextInstance(Instances) - Method in class weka.core.converters.CSVLoader

getNextInstance(Instances) - Method in class weka.core.converters.DatabaseLoader

Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.

getNextInstance(Instances) - Method in class weka.core.converters.JSONLoader

JSONLoader is unable to process a data set incrementally.

getNextInstance(Instances) - Method in class weka.core.converters.LibSVMLoader

LibSVmLoader is unable to process a data set incrementally.

getNextInstance(Instances) - Method in interface weka.core.converters.Loader

Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.

getNextInstance(Instances) - Method in class weka.core.converters.MatlabLoader

MatlabLoader is unable to process a data set incrementally.

getNextInstance(Instances) - Method in class weka.core.converters.SerializedInstancesLoader

Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.

getNextInstance(Instances) - Method in class weka.core.converters.SVMLightLoader

SVMLightLoader is unable to process a data set incrementally.

getNextInstance(Instances) - Method in class weka.core.converters.TextDirectoryLoader

Process input directories/files incrementally.

getNextInstance(Instances) - Method in class weka.core.converters.XRFFLoader

XRFFLoader is unable to process a data set incrementally.

getNGramMaxSize() - Method in class weka.core.tokenizers.NGramTokenizer

Gets the max N of the NGram.

getNGramMinSize() - Method in class weka.core.tokenizers.NGramTokenizer

Gets the min N of the NGram.

getNoClass() - Method in class weka.core.TestInstances

whether no class attribute is generated

getNode(String) - Method in class weka.classifiers.bayes.net.BIFReader

getNode finds the index of the node with name sNodeName and throws an exception if no such node can be found.

getNode(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns index of node with given name.

getNode(String) - Method in class weka.classifiers.bayes.net.MarginCalculator

getNode() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the node property.

getNode(String) - Method in class weka.core.xml.XMLDocument

Returns the node represented by the XPath expression.

getNode2(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns index of node with given name, or -1 if no such node exists

getNodeName(int) - Method in class weka.classifiers.bayes.BayesNet

get name of a node in the Bayes network

getNodes() - Method in class weka.classifiers.trees.lmt.LMTNode

Return a list of all inner nodes in the tree

getNodes(Vector<LMTNode>) - Method in class weka.classifiers.trees.lmt.LMTNode

Fills a list with all inner nodes in the tree

getNodes() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

give access to set of graph nodes

getNodes() - Method in interface weka.gui.graphvisualizer.LayoutEngine

give access to set of graph nodes

getNodeSplitter() - Method in class weka.core.neighboursearch.KDTree

Returns the splitting method currently in use to split the nodes of the KDTree.

getNodeType() - Method in class weka.core.json.JSONNode

Returns the type of the container.

getNodeValue(int, int) - Method in class weka.classifiers.bayes.BayesNet

get name of a particular value of a node

getNoHeaderRow() - Method in class weka.core.converters.CSVSaver

Get whether to not write the header row

getNoHeaderRowPresent() - Method in class weka.core.converters.CSVLoader

Get whether there is no header row in the data.

getNoise() - Method in class weka.classifiers.functions.GaussianProcesses

Get the value of noise.

getNoisePercent() - Method in class weka.datagenerators.classifiers.classification.LED24

Gets the noise percentage.

getNoiseRate() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the gaussian noise rate.

getNoiseRate() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the percentage of noise set.

getNoiseRate() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Gets the percentage of noise set.

getNoiseVariance() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the noise variance

getNominalAttributes() - Method in class weka.core.converters.CSVLoader

Returns the current attribute range to be forced to type nominal.

getNominalBinary() - Method in class weka.gui.beans.SubstringLabeler

Get whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.

getNominalBinary() - Method in class weka.gui.beans.SubstringLabelerRules

Get whether to create a nominal binary attribute in the case when the user has not supplied an explicit label to use for each rule.

getNominalCols() - Method in class weka.datagenerators.ClusterGenerator

returns the range of nominal attributes

getNominalIndices() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Get the set of nominal value indices that will be used for selection

getNominalLabels() - Method in class weka.filters.unsupervised.attribute.Add

Get the list of labels for nominal attribute creation.

getNominalLabelSpecs() - Method in class weka.core.converters.CSVLoader

Get label specifications for nominal attributes.

getNominalOrStringValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the value of the attribute as a string (nominal and string attribute) or null if the attribute is not nominal or string

getNominalStringReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Get the nominal/string replacement value

getNominalToBinaryFilter() - Method in class weka.classifiers.functions.MultilayerPerceptron

getNoPruning() - Method in class weka.classifiers.trees.REPTree

Get the value of NoPruning.

getNoReplacement() - Method in class weka.filters.supervised.instance.Resample

Gets whether instances are drawn with or without replacement.

getNoReplacement() - Method in class weka.filters.unsupervised.instance.Resample

Gets whether instances are drawn with or without replacement.

getNorm() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get the instance's Norm.

getNorm() - Method in class weka.classifiers.functions.SGDText

Get the instance's Norm.

getNorm() - Method in class weka.core.pmml.jaxbbindings.LinearNorm

Gets the value of the norm property.

getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the normalizationMethod property.

getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the normalizationMethod property.

getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the normalizationMethod property.

getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the normalizationMethod property.

getNormalizationScheme() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the normalizationScheme property.

getNormalizeAttributes() - Method in class weka.classifiers.functions.MultilayerPerceptron

getNormalizedCountTable() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the normalizedCountTable property.

getNormalizeDimWidths() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Whether we are normalizing the widths(ranges) of the dimensions (attributes) or not.

getNormalizeDocLength() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get whether to normalize the length of each document

getNormalizeDocLength() - Method in class weka.classifiers.functions.SGDText

Get whether to normalize the length of each document

getNormalizeDocLength() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether if the word frequencies for a document (instance) should be normalized or not.

getNormalizeNodeWidth() - Method in class weka.core.neighboursearch.KDTree

Gets the normalize flag.

getNormalizeNumericClass() - Method in class weka.classifiers.functions.MultilayerPerceptron

getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the normContinuous property.

getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the normContinuous property.

getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the normContinuous property.

getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the normDiscrete property.

getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the normDiscrete property.

getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the normDiscrete property.

getNoSizeDetermination() - Method in class weka.experiment.ClassifierSplitEvaluator

Returns whether the size determination (train/test/classifer) is skipped.

getNoSizeDetermination() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns whether the size determination (train/test/clusterer) is skipped.

getNoSizeDetermination() - Method in class weka.experiment.RegressionSplitEvaluator

Returns whether the size determination (train/test/classifer) is skipped.

getNot() - Method in class weka.datagenerators.Test

Negates the test.

getNotCapabilities() - Method in class weka.core.FindWithCapabilities

The "not to have" capabilities to search for.

getNotes() - Method in class weka.experiment.Experiment

Get the user notes.

getNoteText() - Method in class weka.gui.beans.Note

Get the note text

getNoTrueChildStrategy() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the noTrueChildStrategy property.

getNoTrueChildStrategy() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the noTrueChildStrategy property.

getNPointPrecision(Instances, int) - Static method in class weka.classifiers.evaluation.ThresholdCurve

Calculates the n point precision result, which is the precision averaged over n evenly spaced (w.r.t recall) samples of the curve.

getNrOfGoodOperations() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Gets the number of "good operations"

getNrOfLookAheadSteps() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Gets the number of look-ahead steps

getNrOfNodes() - Method in class weka.classifiers.bayes.BayesNet

get number of nodes in the Bayes network

getNrOfParents(int) - Method in class weka.classifiers.bayes.BayesNet

get number of parents of a node in the network structure

getNrOfParents() - Method in class weka.classifiers.bayes.net.ParentSet

returns number of parents

getNumArcs() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Gets the number of arcs for the bayesian net

getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.ContStats

Gets the value of the numarray property.

getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the numarray property.

getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the numarray property.

getNumAttributes() - Method in class weka.core.TestInstances

returns the overall number of attributes (incl.

getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Gets the number of attributes that should be produced.

getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Gets the number of attributes that should be produced.

getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the number of attributes that should be produced.

getNumAttributes() - Method in class weka.datagenerators.ClusterGenerator

Gets the number of attributes that should be produced.

getNumAttributes() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Get the number of attributes (< 1 percentage, >= 1 absolute number).

getNumberOfAttributes() - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Gets the value of the numberOfAttributes property.

getNumberOfAttributes() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Gets the current number of attributes (dimensionality) to which the data will be reduced to.

getNumberOfClusters() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the numberOfClusters property.

getNumberOfCoefficients() - Method in class weka.core.pmml.jaxbbindings.Coefficients

Gets the value of the numberOfCoefficients property.

getNumberOfDocuments() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the numberOfDocuments property.

getNumberOfFields() - Method in class weka.core.pmml.jaxbbindings.DataDictionary

Gets the value of the numberOfFields property.

getNumberOfFields() - Method in class weka.core.pmml.jaxbbindings.VectorFields

Gets the value of the numberOfFields property.

getNumberOfInputs() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs

Gets the value of the numberOfInputs property.

getNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the numberOfItems property.

getNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Itemset

Gets the value of the numberOfItems property.

getNumberOfItemsets() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the numberOfItemsets property.

getNumberOfLayers() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the numberOfLayers property.

getNumberOfMetricsForRule() - Method in class weka.associations.AssociationRule

Gets the number of metrics available for this rule.

getNumberOfMetricsForRule() - Method in class weka.associations.DefaultAssociationRule

getNumberOfNeighbors() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the numberOfNeighbors property.

getNumberOfNeurons() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the numberOfNeurons property.

getNumberOfOutputs() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs

Gets the value of the numberOfOutputs property.

getNumberOfRules() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the numberOfRules property.

getNumberOfSets() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the numberOfSets property.

getNumberOfSets() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the numberOfSets property.

getNumberOfSupportVectors() - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Gets the value of the numberOfSupportVectors property.

getNumberOfTerms() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the numberOfTerms property.

getNumberOfTransactionGroups() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the numberOfTransactionGroups property.

getNumberOfTransactions() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the numberOfTransactions property.

getNumberOfTransactions() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the numberOfTransactions property.

getNumberOfVectors() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Gets the value of the numberOfVectors property.

getNumBins() - Method in class weka.classifiers.meta.RegressionByDiscretization

Gets the number of bins numeric attributes will be divided into

getNumBins() - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats

getNumBins() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Gets the number of bins

getNumBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of numBoostingIterations.

getNumBoostingIterations() - Method in class weka.classifiers.trees.LMT

Get the value of numBoostingIterations.

getNumCentroids() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Gets the number of centroids.

getNumClasses() - Method in class weka.core.TestInstances

returns the current number of classes

getNumClasses() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Gets the number of classes the dataset should have.

getNumClasses() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the number of classes the dataset should have.

getNumClusters() - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator

Return the number of clusters used by the subset evaluator

getNumClusters() - Method in class weka.clusterers.Canopy

Get the number of clusters to generate

getNumClusters() - Method in class weka.clusterers.ClusterEvaluation

Return the number of clusters found for the most recent call to evaluateClusterer

getNumClusters() - Method in class weka.clusterers.EM

Get the number of clusters

getNumClusters() - Method in class weka.clusterers.FarthestFirst

gets the number of clusters to generate

getNumClusters() - Method in class weka.clusterers.HierarchicalClusterer

getNumClusters() - Method in class weka.clusterers.SimpleKMeans

gets the number of clusters to generate.

getNumClusters() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the number of clusters the dataset should have.

getNumCycles() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the number of cycles.

getNumDatasets() - Method in class weka.experiment.PairedTTester

Gets the number of datasets in the resultsets

getNumDatasets() - Method in interface weka.experiment.Tester

Gets the number of datasets in the resultsets

getNumDate() - Method in class weka.core.CheckScheme

returns the current number of date attributes

getNumDate() - Method in class weka.core.TestInstances

returns the current number of date attributes

getNumDecimals() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the number of digits to output after the decimal point.

getNumeric() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Check if new attribute is to be numeric.

getNumericColumns() - Method in class weka.gui.sql.ResultSetHelper

returns an array that indicates whether a column is numeric or nor.

getNumericInfo() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the numericInfo property.

getNumericInfo() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the numericInfo property.

getNumericPredictors() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the numericPredictor property.

getNumericReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Get the numeric replacement value

getNumericValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the value of the attribute as a number or Utils.missingValue() if the attribute is not numeric.

getNumExamples() - Method in class weka.datagenerators.ClassificationGenerator

Gets the number of examples, given by option.

getNumExamples() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Gets the number of examples, given by option.

getNumExamples() - Method in class weka.datagenerators.RegressionGenerator

Gets the number of examples, given by option.

getNumExamplesAct() - Method in class weka.datagenerators.DataGenerator

Gets the number of examples the dataset should have.

getNumExecutionSlots() - Method in class weka.attributeSelection.GreedyStepwise

Gets the number of threads.

getNumExecutionSlots() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Get the number of execution slots (threads) to use for building the members of the ensemble.

getNumExecutionSlots() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Get the number of execution slots (threads) to use for building the members of the ensemble.

getNumExecutionSlots() - Method in class weka.classifiers.trees.RandomForest

Get the number of execution slots (threads) to use for building the members of the ensemble.

getNumExecutionSlots() - Method in class weka.clusterers.EM

Get the degree of parallelism to use.

getNumExecutionSlots() - Method in class weka.clusterers.SimpleKMeans

Get the degree of parallelism to use.

getNumFeatures() - Method in class weka.classifiers.trees.RandomForest

Get the number of features used in random selection.

getNumFiles() - Method in class weka.core.Debug.Log

returns the number of files being used

getNumFolds() - Method in class weka.classifiers.functions.SMO

Get the value of numFolds.

getNumFolds() - Method in class weka.classifiers.meta.CVParameterSelection

Gets the number of folds for the cross-validation.

getNumFolds() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Get the value of NumFolds.

getNumFolds() - Method in class weka.classifiers.meta.MultiScheme

Gets the number of folds for cross-validation.

getNumFolds() - Method in class weka.classifiers.meta.Stacking

Gets the number of folds for the cross-validation.

getNumFolds() - Method in class weka.classifiers.rules.PART

Get the value of numFolds.

getNumFolds() - Method in class weka.classifiers.trees.J48

Get the value of numFolds.

getNumFolds() - Method in class weka.classifiers.trees.RandomTree

Get the value of NumFolds.

getNumFolds() - Method in class weka.classifiers.trees.REPTree

Get the value of NumFolds.

getNumFolds() - Method in class weka.clusterers.EM

Get the number of folds to use when cross-validating to find the best number of clusters.

getNumFolds() - Method in class weka.experiment.CrossValidationResultProducer

Get the value of NumFolds.

getNumFolds() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets the number of folds in which dataset is to be split into.

getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets the number of folds in which dataset is to be split into.

getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the number of cross-validation folds used by the filter.

getNumGeneratingModels() - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Returns the number of generating models used by this DataGenerator

getNumGeneratingModels() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Return the number of kernels (there is one per training instance)

getNumInnerNodes() - Method in class weka.classifiers.trees.lmt.LMTNode

Method to count the number of inner nodes in the tree

getNumInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

getNumInstances() - Method in class weka.classifiers.bayes.BayesNet

Returns the number of instances the model was built from.

getNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode

Return the number of instances that reach this node.

getNumInstances() - Method in class weka.core.CheckScheme

Gets the current number of instances to use for the datasets.

getNumInstances() - Method in class weka.core.TestInstances

returns the current number of instances to produce

getNumInstances() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getNumInstances() - Method in class weka.estimators.CheckEstimator

Gets the current number of instances to use for the datasets.

getNumInstancesRelational() - Method in class weka.core.CheckScheme

returns the current number of instances in relational/bag attributes to produce

getNumInstancesRelational() - Method in class weka.core.TestInstances

returns the current number of instances in relational/bag attributes to produce

getNumIrrelevant() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the number of irrelevant attributes.

getNumIterations() - Method in class weka.classifiers.functions.VotedPerceptron

Get the value of NumIterations.

getNumIterations() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Gets the number of bagging iterations

getNumKernels() - Method in class weka.estimators.KernelEstimator

Return the number of kernels in this kernel estimator

getNumLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns the number of leaves in the tree.

getNumLeaves() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the number of leaves in the built tree.

getNumNeighbours() - Method in class weka.attributeSelection.ReliefFAttributeEval

Get the number of nearest neighbours

getNumNodes() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the number of nodes (internal + leaf) in the built tree.

getNumNominal() - Method in class weka.core.CheckScheme

returns the current number of nominal attributes

getNumNominal() - Method in class weka.core.TestInstances

returns the current number of nominal attributes

getNumNominalValues() - Method in class weka.core.TestInstances

returns the current number of values for nominal attributes

getNumNumeric() - Method in class weka.core.CheckScheme

returns the current number of numeric attributes

getNumNumeric() - Method in class weka.core.TestInstances

returns the current number of numeric attributes

getNumNumeric() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the number of numerical attributes.

getNumOfPredictors() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the numOfPredictors property.

getNumOfRecords() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the numOfRecords property.

getNumOfRecordsWeighted() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the numOfRecordsWeighted property.

getNumOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

getNumQueries() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the number of queries.

getNumRegressions() - Method in class weka.classifiers.functions.SimpleLogistic

Get the number of LogitBoost iterations performed (= the number of regression functions fit by LogitBoost).

getNumRegressions() - Method in class weka.classifiers.trees.lmt.LogisticBase

The number of LogitBoost iterations performed (= the number of simple regression functions fit).

getNumRelational() - Method in class weka.core.CheckScheme

returns the current number of relational attributes

getNumRelational() - Method in class weka.core.TestInstances

returns the current number of relational attributes

getNumRelationalDate() - Method in class weka.core.TestInstances

returns the current number of date attributes in a relational attribute

getNumRelationalNominal() - Method in class weka.core.TestInstances

returns the current number of nominal attributes in a relational attribute

getNumRelationalNominalValues() - Method in class weka.core.TestInstances

returns the current number of values for nominal attributes in a relational attribute

getNumRelationalNumeric() - Method in class weka.core.TestInstances

returns the current number of numeric attributes in a relational attribute

getNumRelationalString() - Method in class weka.core.TestInstances

returns the current number of string attributes in a relational attribute

getNumResultsets() - Method in class weka.experiment.PairedTTester

Gets the number of resultsets in the data.

getNumResultsets() - Method in interface weka.experiment.Tester

Gets the number of resultsets in the data.

getNumRules() - Method in class weka.associations.Apriori

Get the value of numRules.

getNumRules() - Method in class weka.associations.AssociationRules

Get the number of rules.

getNumRules() - Method in class weka.associations.FilteredAssociationRules

Get the number of rules.

getNumRulesToFind() - Method in class weka.associations.FPGrowth

Get the number of rules to find.

getNumRuns() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Get the value of NumRuns.

getNumSamplesPerRegion() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Get the number of points to sample from a region (fixed dimensions).

getNumString() - Method in class weka.core.CheckScheme

returns the current number of string attributes

getNumString() - Method in class weka.core.TestInstances

returns the current number of string attributes

getNumSymbols() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Gets the number of symbols this estimator operates with

getNumSymbols() - Method in class weka.estimators.DiscreteEstimator

Gets the number of symbols this estimator operates with

getNumTabs() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getNumThreads() - Method in class weka.attributeSelection.CfsSubsetEval

Gets the number of threads.

getNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise

Gets the number of attributes to be retained.

getNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch

Gets the user specified number of attributes to be retained.

getNumToSelect() - Method in class weka.attributeSelection.Ranker

Gets the number of attributes to be retained.

getNumTraining() - Method in class weka.classifiers.lazy.IBk

Get the number of training instances the classifier is currently using.

getNumTrees() - Method in class weka.classifiers.trees.RandomForest

Get the value of numTrees.

getNumValues() - Method in class weka.datagenerators.clusterers.SubspaceCluster

returns array that stores the number of values for a nominal attribute.

getNumValues() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Gets how many values are retained

getObject() - Method in class weka.core.CheckGOE

Get the object used in the tests.

getObject() - Method in class weka.core.SerializedObject

Returns a serialized object.

getOccurrence() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the occurrence property.

getOccurrence() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the occurrence property.

getOffDiagDefault() - Method in class weka.core.pmml.jaxbbindings.Matrix

Gets the value of the offDiagDefault property.

getOffscreenAdditionalOpts() - Method in class weka.gui.beans.DataVisualizer

Get the additional options for the offscreen renderer

getOffscreenAdditionalOpts() - Method in class weka.gui.beans.ModelPerformanceChart

Get the additional options for the offscreen renderer

getOffscreenHeight() - Method in class weka.gui.beans.DataVisualizer

Get the height (in pixels) of the offscreen image to generate

getOffscreenHeight() - Method in class weka.gui.beans.ModelPerformanceChart

Get the height (in pixels) of the offscreen image to generate

getOffscreenRendererName() - Method in class weka.gui.beans.DataVisualizer

Get the name of the renderer to use for offscreen chart rendering operations

getOffscreenRendererName() - Method in class weka.gui.beans.ModelPerformanceChart

Get the name of the renderer to use for offscreen chart rendering operations

getOffscreenWidth() - Method in class weka.gui.beans.DataVisualizer

Get the width (in pixels) of the offscreen image to generate.

getOffscreenWidth() - Method in class weka.gui.beans.ModelPerformanceChart

Get the width (in pixels) of the offscreen image to generate.

getOffscreenXAxis() - Method in class weka.gui.beans.DataVisualizer

Get the name of the attribute for the x-axis in offscreen plots

getOffscreenXAxis() - Method in class weka.gui.beans.ModelPerformanceChart

Get the name of the attribute for the x-axis in offscreen plots

getOffscreenYAxis() - Method in class weka.gui.beans.DataVisualizer

Get the name of the attribute for the y-axix of offscreen plots.

getOffscreenYAxis() - Method in class weka.gui.beans.ModelPerformanceChart

Get the name of the attribute for the y-axix of offscreen plots.

getOffset() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the offset property.

getOffsetValue() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the offsetValue property.

getOffsetVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the offsetVariable property.

getOmega() - Method in class weka.classifiers.functions.supportVector.Puk

Gets the omega value.

getOnDemandDirectory() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns the directory that will be searched for cost files when loading on demand.

getOnDemandDirectory() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns the directory that will be searched for cost files when loading on demand.

getOperator() - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Gets the value of the operator property.

getOperator() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Gets the value of the operator property.

getOptimizations() - Method in class weka.classifiers.rules.JRip

Gets the the number of optimization runs

getOptimumLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the optimumLiftGraph property.

getOption(char, String[]) - Static method in class weka.core.Utils

Gets an option indicated by a flag "-Char" from the given array of strings.

getOption(String, String[]) - Static method in class weka.core.Utils

Gets an option indicated by a flag "-String" from the given array of strings.

getOptionHandler() - Method in class weka.core.CheckOptionHandler

Get the OptionHandler used in the tests.

getOptionPos(char, String[]) - Static method in class weka.core.Utils

Gets the index of an option or flag indicated by a flag "-Char" from the given array of strings.

getOptionPos(String, String[]) - Static method in class weka.core.Utils

Gets the index of an option or flag indicated by a flag "-String" from the given array of strings.

getOptions() - Method in class weka.associations.Apriori

Gets the current settings of the Apriori object.

getOptions() - Method in class weka.associations.CheckAssociator

Gets the current settings of the CheckAssociator.

getOptions() - Method in class weka.associations.FilteredAssociator

Gets the current settings of the Associator.

getOptions() - Method in class weka.associations.FPGrowth

Gets the current settings of the classifier.

getOptions() - Method in class weka.associations.SingleAssociatorEnhancer

Gets the current settings of the associator.

getOptions() - Method in class weka.attributeSelection.BestFirst

Gets the current settings of BestFirst.

getOptions() - Method in class weka.attributeSelection.CfsSubsetEval

Gets the current settings of CfsSubsetEval

getOptions() - Method in class weka.attributeSelection.CheckAttributeSelection

Gets the current settings of the CheckAttributeSelection.

getOptions() - Method in class weka.attributeSelection.CorrelationAttributeEval

Gets the current settings of WrapperSubsetEval.

getOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval

Gets the current settings of WrapperSubsetEval.

getOptions() - Method in class weka.attributeSelection.GreedyStepwise

Gets the current settings of ReliefFAttributeEval.

getOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval

Gets the current settings of WrapperSubsetEval.

getOptions() - Method in class weka.attributeSelection.OneRAttributeEval

returns the current setup.

getOptions() - Method in class weka.attributeSelection.PrincipalComponents

Gets the current settings of PrincipalComponents

getOptions() - Method in class weka.attributeSelection.Ranker

Gets the current settings of ReliefFAttributeEval.

getOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval

Gets the current settings of ReliefFAttributeEval.

getOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Gets the current settings of WrapperSubsetEval.

getOptions() - Method in class weka.attributeSelection.WrapperSubsetEval

Gets the current settings of WrapperSubsetEval.

getOptions() - Method in class weka.classifiers.AbstractClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.bayes.BayesNet

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.NaiveBayes

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.K2

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.K2

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Gets the current settings of the search algorithm.

getOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.BVDecompose

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.classifiers.CheckClassifier

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.classifiers.CheckSource

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.evaluation.output.prediction.CSV

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.functions.GaussianProcesses

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.LinearRegression

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.Logistic

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron

Gets the current settings of NeuralNet.

getOptions() - Method in class weka.classifiers.functions.SGD

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.SGDText

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.SimpleLinearRegression

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.SimpleLogistic

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.functions.SMO

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.SMOreg

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.supportVector.CachedKernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.CheckKernel

Gets the current settings of the CheckKernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.Kernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.Puk

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.supportVector.RegSMO

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Gets the current settings of the object.

getOptions() - Method in class weka.classifiers.functions.supportVector.StringKernel

Gets the current settings of the Kernel.

getOptions() - Method in class weka.classifiers.functions.VotedPerceptron

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.lazy.IBk

Gets the current settings of IBk.

getOptions() - Method in class weka.classifiers.lazy.KStar

Gets the current settings of K*.

getOptions() - Method in class weka.classifiers.lazy.LWL

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.AdaBoostM1

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.AdditiveRegression

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.Bagging

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.CVParameterSelection

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.FilteredClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.LogitBoost

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.MultiClassClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.MultiScheme

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.RandomSubSpace

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.Stacking

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.Vote

Gets the current settings of Vote.

getOptions() - Method in class weka.classifiers.misc.InputMappedClassifier

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.misc.SerializedClassifier

returns the options of the current setup

getOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableClassifier

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.rules.DecisionTable

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.rules.JRip

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.rules.OneR

Gets the current settings of the OneR classifier.

getOptions() - Method in class weka.classifiers.rules.PART

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.SingleClassifierEnhancer

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.trees.HoeffdingTree

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.trees.J48

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.trees.LMT

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.trees.m5.M5Base

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.trees.M5P

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.trees.RandomForest

Gets the current settings of the forest.

getOptions() - Method in class weka.classifiers.trees.RandomTree

Gets options from this classifier.

getOptions() - Method in class weka.classifiers.trees.REPTree

Gets options from this classifier.

getOptions() - Method in class weka.clusterers.AbstractClusterer

Gets the current settings of the clusterer.

getOptions() - Method in class weka.clusterers.Canopy

Gets the current settings of Canopy.

getOptions() - Method in class weka.clusterers.CheckClusterer

Gets the current settings of the CheckClusterer.

getOptions() - Method in class weka.clusterers.Cobweb

Gets the current settings of Cobweb.

getOptions() - Method in class weka.clusterers.EM

Gets the current settings of EM.

getOptions() - Method in class weka.clusterers.FarthestFirst

Gets the current settings of FarthestFirst

getOptions() - Method in class weka.clusterers.FilteredClusterer

Gets the current settings of the clusterer.

getOptions() - Method in class weka.clusterers.HierarchicalClusterer

Gets the current settings of the clusterer.

getOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer

Gets the current settings of the clusterer.

getOptions() - Method in class weka.clusterers.RandomizableClusterer

Gets the current settings of the classifier.

getOptions() - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Gets the current settings of the classifier.

getOptions() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Gets the current settings of the classifier.

getOptions() - Method in class weka.clusterers.SimpleKMeans

Gets the current settings of SimpleKMeans.

getOptions() - Method in class weka.clusterers.SingleClustererEnhancer

Gets the current settings of the clusterer.

getOptions() - Method in class weka.core.Check

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.core.CheckGOE

Gets the current settings of the object.

getOptions() - Method in class weka.core.CheckOptionHandler

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.core.CheckScheme

Gets the current settings of the CheckClassifier.

getOptions() - Method in class weka.core.converters.AbstractFileSaver

Gets the current settings of the Saver object.

getOptions() - Method in class weka.core.converters.ArffSaver

returns the options of the current setup

getOptions() - Method in class weka.core.converters.C45Saver

Gets the current settings of the C45Saver object.

getOptions() - Method in class weka.core.converters.CSVLoader

getOptions() - Method in class weka.core.converters.CSVSaver

Gets the current settings of the Classifier.

getOptions() - Method in class weka.core.converters.DatabaseLoader

Gets the setting

getOptions() - Method in class weka.core.converters.DatabaseSaver

Gets the setting.

getOptions() - Method in class weka.core.converters.JSONSaver

returns the options of the current setup.

getOptions() - Method in class weka.core.converters.LibSVMSaver

returns the options of the current setup

getOptions() - Method in class weka.core.converters.MatlabSaver

returns the options of the current setup.

getOptions() - Method in class weka.core.converters.SVMLightSaver

returns the options of the current setup.

getOptions() - Method in class weka.core.converters.TextDirectoryLoader

Gets the setting

getOptions() - Method in class weka.core.converters.XRFFSaver

returns the options of the current setup

getOptions() - Method in class weka.core.FindWithCapabilities

Gets the current settings of this object.

getOptions() - Method in class weka.core.Javadoc

Gets the current settings of this object.

getOptions() - Method in class weka.core.ListOptions

Gets the current settings of this object.

getOptions() - Method in class weka.core.MinkowskiDistance

Gets the current settings of this object.

getOptions() - Method in class weka.core.neighboursearch.BallTree

Gets the current settings of KDtree.

getOptions() - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Gets the current settings of the object.

getOptions() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Gets the current settings.

getOptions() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Gets the current settings of the object.

getOptions() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Gets the current settings.

getOptions() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Gets the current settings of this BallTree MiddleOutConstructor.

getOptions() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Gets the current settings of KDtree.

getOptions() - Method in class weka.core.neighboursearch.CoverTree

Gets the current settings of KDtree.

getOptions() - Method in class weka.core.neighboursearch.KDTree

Gets the current settings of KDtree.

getOptions() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Gets the current settings of the object.

getOptions() - Method in class weka.core.neighboursearch.LinearNNSearch

Gets the current settings.

getOptions() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Gets the current settings.

getOptions() - Method in class weka.core.NormalizableDistance

Gets the current settings.

getOptions() - Method in interface weka.core.OptionHandler

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.OptionHandlerJavadoc

Gets the current settings of this object.

getOptions() - Method in class weka.core.stemmers.SnowballStemmer

Gets the current settings of the classifier.

getOptions() - Method in class weka.core.TechnicalInformationHandlerJavadoc

Gets the current settings of this object.

getOptions() - Method in class weka.core.TestInstances

Gets the current settings of this object.

getOptions() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.NGramTokenizer

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.Tokenizer

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.datagenerators.ClassificationGenerator

Gets the current settings of the classifier.

getOptions() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Gets the current settings of the datagenerator.

getOptions() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Gets the current settings of the datagenerator.

getOptions() - Method in class weka.datagenerators.classifiers.classification.LED24

Gets the current settings of the datagenerator.

getOptions() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Gets the current settings of the datagenerator.

getOptions() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the current settings of the datagenerator RDG1.

getOptions() - Method in class weka.datagenerators.classifiers.regression.Expression

Gets the current settings of the datagenerator BIRCHCluster.

getOptions() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Gets the current settings of the datagenerator BIRCHCluster.

getOptions() - Method in class weka.datagenerators.ClusterDefinition

Gets the current settings of the datagenerator BIRCHCluster.

getOptions() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the current settings of the datagenerator BIRCHCluster.

getOptions() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Gets the current settings of the datagenerator.

getOptions() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Gets the current settings of the datagenerator BIRCHCluster.

getOptions() - Method in class weka.datagenerators.ClusterGenerator

Gets the current settings of the classifier.

getOptions() - Method in class weka.datagenerators.DataGenerator

Gets the current settings of the datagenerator RDG1.

getOptions() - Method in class weka.datagenerators.RegressionGenerator

Gets the current settings of the classifier.

getOptions() - Method in class weka.estimators.CheckEstimator

Gets the current settings of the CheckEstimator.

getOptions() - Method in class weka.estimators.Estimator

Gets the current settings of the Estimator.

getOptions() - Method in class weka.experiment.AveragingResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the current settings of the Classifier.

getOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Gets the current settings of the Classifier.

getOptions() - Method in class weka.experiment.CrossValidationResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.CSVResultListener

Gets the current settings of the Classifier.

getOptions() - Method in class weka.experiment.DatabaseResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the current settings of the Classifier.

getOptions() - Method in class weka.experiment.Experiment

Gets the current settings of the experiment iterator.

getOptions() - Method in class weka.experiment.ExplicitTestsetResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.InstanceQuery

Gets the current settings of InstanceQuery

getOptions() - Method in class weka.experiment.LearningRateResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.PairedTTester

Gets current settings of the PairedTTester.

getOptions() - Method in class weka.experiment.RandomSplitResultProducer

Gets the current settings of the result producer.

getOptions() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the current settings of the Classifier.

getOptions() - Method in class weka.experiment.ResultMatrix

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.CheckSource

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.MultiFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.SimpleFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.attribute.AddClassification

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection

Gets the current settings for the attribute selection (search, evaluator) etc.

getOptions() - Method in class weka.filters.supervised.attribute.ClassOrder

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.attribute.Discretize

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.attribute.PartitionMembership

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.instance.Resample

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.Add

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AddID

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AddUserFields

Gets the current settings of the filter

getOptions() - Method in class weka.filters.unsupervised.attribute.AddValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.Copy

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MathExpression

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToString

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.Normalize

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.Remove

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveByName

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

getOptions() - Method in class weka.filters.unsupervised.attribute.Reorder

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

getOptions() - Method in class weka.filters.unsupervised.attribute.SortLabels

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

getOptions() - Method in class weka.filters.unsupervised.instance.Randomize

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.Resample

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Gets the current settings of the filter.

getOptions() - Method in class weka.gui.explorer.AbstractPlotInstances

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.gui.Main

returns the options of the current setup.

getOptions() - Method in class weka.gui.scripting.Script

Gets the current settings of the script.

getOPTYPE(int) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

Returns an OPTYPE for a weka attribute type.

getOptype() - Method in class weka.core.pmml.Expression

Get the optype of the result of applying this Expression.

getOptype() - Method in class weka.core.pmml.FieldMetaInfo

Get the optype.

getOptype() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.ParameterField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the optype property.

getOptype() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the optype property.

getOrder() - Method in enum weka.core.logging.Logger.Level

Returns the order of this level.

getOrder() - Method in class weka.core.MinkowskiDistance

Gets the order.

getOrderedFlag() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the ordered flag (option O).

getOrig() - Method in class weka.core.pmml.jaxbbindings.LinearNorm

Gets the value of the orig property.

getOriginalCoords() - Method in class weka.gui.beans.MetaBean

returns the vector containing the original coordinates (instances of class Point) for the inputs

getOtherCapabilities() - Method in class weka.core.Capabilities

returns all other capabilities, besides class and attribute related ones

getOutlierFactor() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets the factor for determining the thresholds for outliers.

getOutliers() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the outliers property.

getOutliers() - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Gets the value of the outliers property.

getOutlierTreatmentMethod() - Method in class weka.core.pmml.MiningFieldMetaInfo

Get the outlier treatment method used for this field.

getOutput() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the output property.

getOutput() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the output property.

getOutput() - Method in class weka.datagenerators.DataGenerator

Gets the print writer.

getOutput() - Method in class weka.gui.explorer.DataGeneratorPanel

returns the generated output as text

getOutput() - Method in class weka.gui.scripting.FileScriptingPanel

Returns the text area that is used for displaying output on stdout and stderr.

getOutput() - Method in class weka.gui.scripting.ScriptingPanel

Returns the text area that is used for displaying output on stdout and stderr.

getOutput() - Method in class weka.gui.SimpleCLIPanel

Returns the text area that is used for displaying output on stdout and stderr.

getOutputAdditionalStats() - Method in class weka.classifiers.functions.LinearRegression

Get whether to output additional statistics (such as std.

getOutputAdditionalStats() - Method in class weka.classifiers.functions.SimpleLinearRegression

Get whether to output additional statistics (such as std.

getOutputClassification() - Method in class weka.filters.supervised.attribute.AddClassification

Get whether the classifiction of the classifier is output.

getOutputColumn() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the outputColumn property.

getOutputDef() - Method in class weka.core.pmml.BuiltInArithmetic

Get the structure of the result produced by this function.

getOutputDef() - Method in class weka.core.pmml.BuiltInMath

Get the structure of the result produced by this function.

getOutputDef() - Method in class weka.core.pmml.BuiltInString

Get the structure of the result produced by this function.

getOutputDef() - Method in class weka.core.pmml.DefineFunction

Get the structure of the result produced by this function.

getOutputDef() - Method in class weka.core.pmml.FieldRef

Return the structure of the result of applying this Expression as an Attribute.

getOutputDef() - Method in class weka.core.pmml.Function

Get the structure of the result produced by this function.

getOutputDetailedInfo() - Method in class weka.attributeSelection.CorrelationAttributeEval

Get whether to output per-value correlation for nominal attributes

getOutputDistribution() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns whether to output the class distribution as well.

getOutputDistribution() - Method in class weka.filters.supervised.attribute.AddClassification

Get whether the classifiction of the classifier is output.

getOutputErrorFlag() - Method in class weka.filters.supervised.attribute.AddClassification

Get whether the classifiction of the classifier is output.

getOutputFields() - Method in class weka.core.pmml.jaxbbindings.Output

Gets the value of the outputField property.

getOutputFile() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the output file to write to.

getOutputFile() - Method in class weka.experiment.CrossValidationResultProducer

Get the value of OutputFile.

getOutputFile() - Method in class weka.experiment.CSVResultListener

Get the value of OutputFile.

getOutputFile() - Method in class weka.experiment.ExplicitTestsetResultProducer

Get the value of OutputFile.

getOutputFile() - Method in class weka.experiment.RandomSplitResultProducer

Get the value of OutputFile.

getOutputFilename() - Method in class weka.core.converters.TextDirectoryLoader

Gets whether the filename will be stored as an extra attribute.

getOutputFilename() - Method in class weka.gui.GenericPropertiesCreator

returns the name of the output file

getOutputFormat() - Method in class weka.core.Debug.Clock

returns the output format

getOutputFormat() - Method in class weka.filters.Filter

Gets the format of the output instances.

getOutputFormat() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Gets the format of the output instances.

getOutputFormat() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the classname (and optional options) of the ResultMatrix class, responsible for the output format.

getOutputItemSets() - Method in class weka.associations.Apriori

Gets whether itemsets are output as well

getOutputNeuron() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput

Gets the value of the outputNeuron property.

getOutputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection

Use this to get easy access to the output numbers.

getOutputOffsetMultiplier() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Gets whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.

getOutputPerClassInfoRetrievalStats() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Get whether per-class information retrieval stats are to be output.

getOutputProbsForSVM() - Method in class weka.classifiers.functions.SGDText

Get whether to fit a logistic regression (itself trained using SGD) to the outputs of the SVM (if an SVM is being learned).

getOutputProperties() - Method in class weka.gui.GenericPropertiesCreator

returns the output properties object (structure like the template, but filled with classes instead of packages)

getOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

Use this to get easy access to the outputs.

getOutputs() - Method in class weka.gui.beans.MetaBean

getOutputStructure() - Method in class weka.gui.beans.SubstringLabelerRules

Get the output structure

getOutputTypes() - Method in class weka.core.Debug.DBO

Gets the current output type selection

getOutputWordCounts() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether output instances contain 0 or 1 indicating word presence, or word counts.

getOverwriteWarning() - Method in class weka.gui.ConverterFileChooser

Returns whether a popup appears with a warning that the file already exists (only save dialog).

getOwner() - Method in class weka.core.Capabilities

returns the owner of this capabilities object

getOwner() - Static method in class weka.core.Copyright

returns the entity owning the copyright

getOwner() - Method in class weka.gui.scripting.Script.ScriptThread

Returns the owner.

getP() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the proportion of instances that are common between two training sets.

getPackage(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

returns the packages part of the partial classname.

getPackageArchiveInfo(String) - Static method in class weka.core.WekaPackageManager

Extract meta data from a package archive

getPackageHome() - Static method in class weka.core.WekaPackageManager

getPackageList(boolean) - Static method in class weka.core.WekaPackageManager

Just get a list of the package names.

getPackageRepositoryURL() - Static method in class weka.core.WekaPackageManager

Get the package repository URL

getPaint() - Method in class weka.gui.visualize.PostscriptGraphics

getPairCounts() - Method in class weka.core.pmml.jaxbbindings.BayesInput

Gets the value of the pairCounts property.

getPanel(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the specified panel, null if index is out of bounds

getPanel() - Method in class weka.gui.scripting.event.TitleUpdatedEvent

Returns the scripting panel that triggered the event.

getPanelCount() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the number of panels currently open

getPanels() - Method in class weka.gui.explorer.Explorer

returns all the panels, apart from the PreprocessPanel

getParameter() - Method in class weka.core.pmml.jaxbbindings.ParameterList

Gets the value of the parameter property.

getParameterField() - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Gets the value of the parameterField property.

getParameterName() - Method in class weka.core.pmml.jaxbbindings.PCell

Gets the value of the parameterName property.

getParameterName() - Method in class weka.core.pmml.jaxbbindings.PPCell

Gets the value of the parameterName property.

getParameterNames() - Method in class weka.core.pmml.BuiltInArithmetic

Returns an array of the names of the parameters expected as input by this function

getParameterNames() - Method in class weka.core.pmml.BuiltInMath

Returns an array of the names of the parameters expected as input by this function.

getParameterNames() - Method in class weka.core.pmml.BuiltInString

Returns an array of the names of the parameters expected as input by this function.

getParameterNames() - Method in class weka.core.pmml.DefineFunction

Returns an array of the names of the parameters expected as input by this function.

getParameterNames() - Method in class weka.core.pmml.Function

Returns an array of the names of the parameters expected as input by this function.

getParent(int, int) - Method in class weka.classifiers.bayes.BayesNet

get node index of a parent of a node in the network structure

getParent(int) - Method in class weka.classifiers.bayes.net.ParentSet

returns index parent of parent specified by index

getParent() - Method in class weka.datagenerators.ClusterDefinition

returns the parent datagenerator this cluster belongs to

getParent(int) - Method in class weka.gui.treevisualizer.Node

Get the parent edge.

getParentCardinality(int) - Method in class weka.classifiers.bayes.BayesNet

get number of values the collection of parents of a node can take

getParentDialog(Container) - Static method in class weka.gui.PropertyDialog

Tries to determine the dialog this panel is part of.

getParentField() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the parentField property.

getParentFrame() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the parent frame, if it's a JFrame, otherwise null

getParentFrame() - Method in class weka.gui.GUIChooser.ChildFrameSDI

returns the parent frame, can be null.

getParentFrame() - Method in class weka.gui.Main.ChildFrameMDI

returns the parent frame, can be null.

getParentFrame() - Method in class weka.gui.Main.ChildFrameSDI

returns the parent frame, can be null.

getParentFrame(Container) - Static method in class weka.gui.PropertyDialog

Tries to determine the frame this panel is part of.

getParentFrame() - Method in class weka.gui.SetInstancesPanel

Returns the current frame the panel knows of, that it resides in.

getParentInternalFrame() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the parent frame, if it's a JInternalFrame, otherwise null

getParentInternalFrame(Container) - Static method in class weka.gui.PropertyDialog

Tries to determine the internal frame this panel is part of.

getParentLevelField() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the parentLevelField property.

getParents() - Method in class weka.classifiers.bayes.net.ParentSet

getParentSet(int) - Method in class weka.classifiers.bayes.BayesNet

get the parent set of a node

getParentSets() - Method in class weka.classifiers.bayes.BayesNet

Get full set of parent sets.

getPartialScore() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the partialScore property.

getPartition() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the partition property.

getPartition() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the partition property.

getPartitionFieldStats() - Method in class weka.core.pmml.jaxbbindings.Partition

Gets the value of the partitionFieldStats property.

getPartitionGenerator() - Method in class weka.filters.supervised.attribute.PartitionMembership

Get the generator used by this filter

getPassword() - Method in class weka.core.converters.DatabaseLoader

Returns the database password

getPassword() - Method in class weka.core.converters.DatabaseSaver

Returns the database password.

getPassword() - Method in class weka.experiment.DatabaseUtils

Get the database password.

getPassword() - Method in class weka.gui.DatabaseConnectionDialog

Returns password from dialog

getPassword() - Method in class weka.gui.sql.ConnectionPanel

returns the current Password.

getPassword() - Method in class weka.gui.sql.event.ResultChangedEvent

returns the password that produced the table model

getPassword() - Method in class weka.gui.sql.ResultSetTable

returns the password that produced the table model

getPassword() - Method in class weka.gui.sql.SqlViewer

returns the password from the currently active tab in the ResultPanel, otherwise an empty string.

getPassword() - Method in class weka.gui.sql.SqlViewerDialog

returns the chosen password, if any.

getPasteBuffer() - Method in class weka.gui.beans.KnowledgeFlowApp

Get the contents of the paste buffer

getPath() - Method in class weka.gui.PropertySelectorDialog

Gets the path of property nodes to the selected property.

getPattern() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the pattern type.

getPCell() - Method in class weka.core.pmml.jaxbbindings.ParamMatrix

Gets the value of the pCell property.

getPCol() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the pCol property.

getPCovCell() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix

Gets the value of the pCovCell property.

getPercent() - Method in class weka.filters.unsupervised.attribute.AddNoise

Gets the size of noise data as a percentage of the original set.

getPercent() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Gets the percent the attributes (dimensions) of the data will be reduced to

getPercentage() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Gets the percentage of instances to select.

getPercentCompleted() - Method in class weka.gui.boundaryvisualizer.RemoteResult

Return the progress for this row

getPerformanceStats() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Gets the class object that contains the performance statistics of the search method.

getPeriod() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the period property.

getPeriodicPruning() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get how often to prune the dictionary

getPeriodicPruning() - Method in class weka.classifiers.functions.SGDText

Get how often to prune the dictionary

getPeriodicPruning() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.

getPeriodicPruningRate() - Method in class weka.clusterers.Canopy

Get the how often to prune low density canopies during training

getPerspectiveIcon() - Method in class weka.gui.beans.AttributeSummarizer

Get the icon for this perspective.

getPerspectiveIcon() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Get the icon for this perspective.

getPerspectiveIcon() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

Get the icon for this perspective

getPerspectiveIcon() - Method in class weka.gui.beans.ScatterPlotMatrix

Get the icon for this perspective.

getPerspectiveIcon() - Method in class weka.gui.beans.SQLViewerPerspective

Get the icon for this perspective.

getPerspectiveTipText() - Method in class weka.gui.beans.AttributeSummarizer

Get the tool tip text for this perspective.

getPerspectiveTipText() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Get the tool tip text for this perspective.

getPerspectiveTipText() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

Get the tool tip text for this perspective

getPerspectiveTipText() - Method in class weka.gui.beans.ScatterPlotMatrix

Get the tool tip text for this perspective.

getPerspectiveTipText() - Method in class weka.gui.beans.SQLViewerPerspective

Get the tool tip text for this perspective.

getPerspectiveTitle() - Method in class weka.gui.beans.AttributeSummarizer

Get the title of this perspective

getPerspectiveTitle() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Get the title of this perspective

getPerspectiveTitle() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

Get the title of this perspective

getPerspectiveTitle() - Method in class weka.gui.beans.ScatterPlotMatrix

Get the title of this perspective

getPerspectiveTitle() - Method in class weka.gui.beans.SQLViewerPerspective

Get the title of this perspective

getPerturbationFraction() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Gets the perturbation fraction.

getPhase() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the phase property.

getPhi() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Gets the value of the phi property.

getPivot() - Method in class weka.core.matrix.LUDecomposition

Return pivot permutation vector

getPivot() - Method in class weka.core.neighboursearch.balltrees.BallNode

Returns the pivot/centre of the node's ball.

getPlainColumnName(int) - Method in class weka.gui.arffviewer.ArffTable

returns the basically the attribute name of the column and not the HTML column name via getColumnName(int)

getPlainTitle() - Method in class weka.gui.scripting.FileScriptingPanel

Returns the title (without the filename).

getPlainTitle() - Method in class weka.gui.scripting.GroovyPanel

Returns the title (without the filename).

getPlainTitle() - Method in class weka.gui.scripting.JythonPanel

Returns the title (without the filename).

getPlotData(String) - Method in class weka.gui.explorer.AbstractPlotInstances

Assembles and returns the plot.

getPlotInstances() - Method in class weka.gui.explorer.AbstractPlotInstances

Returns the generated plot instances.

getPlotInstances() - Method in class weka.gui.visualize.PlotData2D

Returns the instances for this plot

getPlotName() - Method in class weka.gui.visualize.PlotData2D

Get the name of this plot

getPlotNameHTML() - Method in class weka.gui.visualize.PlotData2D

Get the name of the plot for use in a tool tip text.

getPlotPanel() - Method in class weka.gui.visualize.VisualizePanel

Returns the underlying plot panel.

getPlots() - Method in class weka.gui.visualize.Plot2D

Return the list of plots

getPlotShapes() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Get the vector of plot shapes (see weka.gui.visualize.Plot2D).

getPlotSizes() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Get the vector of plot sizes (see weka.gui.visualize.Plot2D).

getPlotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Returns true if training data is to be superimposed

getPluginInstance(String, String) - Static method in class weka.gui.beans.PluginManager

Get an instance of a concrete implementation of a plugin type

getPluginMetric(String) - Method in class weka.classifiers.evaluation.Evaluation

Get the named plugin evaluation metric

getPluginMetric(String) - Method in class weka.classifiers.Evaluation

Get the named plugin evaluation metric

getPluginMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper

Get a list of plugin metric names

getPluginMetrics() - Static method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Gets a list of freshly instantiated concrete implementations of available plugin metrics or null if there are no plugin metrics available

getPluginMetrics() - Method in class weka.classifiers.evaluation.Evaluation

Returns the list of plugin metrics in use (or null if there are none)

getPluginMetrics() - Method in class weka.classifiers.Evaluation

Returns the list of plugin metrics in use (or null if there are none)

getPluginNamesOfType(String) - Static method in class weka.gui.beans.PluginManager

Get a set of names of plugins that implement the supplied interface.

getPMMLModel(String) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLModel(File) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLModel(InputStream) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLModel(String, Logger) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLModel(File, Logger) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLModel(InputStream, Logger) - Static method in class weka.core.pmml.PMMLFactory

Read and return a PMML model.

getPMMLVersion() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Get the PMML version used for this model.

getPMMLVersion() - Method in interface weka.core.pmml.PMMLModel

Get the version of PMML used to encode this model.

getPointSizeProportionalToMargin() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Get whether the point size should be proportional to the prediction margin (classification only).

getPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate

Gets the value of the poissonDistribution property.

getPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the poissonDistribution property.

getPoolSize() - Method in class weka.attributeSelection.CfsSubsetEval

Gets the number of threads.

getPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getPopup() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

returns the currently set JPopupMenu.

getPositionX(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

get x position of a node

getPositionY(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

get y position of a node

getPositiveIndex() - Method in class weka.associations.FPGrowth

Get the index of the attribute value to consider as positive for binary attributes in normal dense instances.

getPositiveTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the positiveTargetFieldDisplayValue property.

getPositiveTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the positiveTargetFieldValue property.

getPossibleSplits(SplitMetric) - Method in class weka.classifiers.trees.ht.ActiveHNode

Returns a list of split candidates

getPostFixExpression() - Method in class weka.core.AttributeExpression

Return the postfix expression

getPostProcessor() - Method in class weka.core.CheckScheme

returns the current PostProcessor, can be null

getPostProcessor() - Method in class weka.estimators.CheckEstimator

returns the current PostProcessor, can be null

getPParameter() - Method in class weka.core.pmml.jaxbbindings.Minkowski

Gets the value of the pParameter property.

getPPCell() - Method in class weka.core.pmml.jaxbbindings.PPMatrix

Gets the value of the ppCell property.

getPRCArea(Instances) - Static method in class weka.classifiers.evaluation.ThresholdCurve

Calculates the area under the precision-recall curve (AUPRC).

getPreBuiltClassifiers() - Method in class weka.classifiers.meta.Vote

Get the paths to pre-built serialized classifiers to load and include in the ensemble

getPrecision() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the precision.

getPrecision() - Method in class weka.core.pmml.jaxbbindings.VerificationField

Gets the value of the precision property.

getPrecision() - Method in class weka.estimators.KernelEstimator

Return the precision of this kernel estimator.

getPrecision() - Method in class weka.estimators.NormalEstimator

Return the value of the precision of this normal estimator.

getPreComputeCorrelationMatrix() - Method in class weka.attributeSelection.CfsSubsetEval

Get whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.

getPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.EvaluationUtils

Generate a single prediction for a test instance given the pre-trained classifier.

getPredictiveModelQuality() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation

Gets the value of the predictiveModelQuality property.

getPredictor() - Method in class weka.core.pmml.jaxbbindings.CovariateList

Gets the value of the predictor property.

getPredictor() - Method in class weka.core.pmml.jaxbbindings.FactorList

Gets the value of the predictor property.

getPredictorName() - Method in class weka.core.pmml.jaxbbindings.PPCell

Gets the value of the predictorName property.

getPredictorTerm() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the predictorTerm property.

getPredTargetColumn() - Method in class weka.experiment.ClassifierSplitEvaluator

getPreferredScrollableViewportSize() - Method in class weka.gui.AttributeSelectionPanel

getPrefix() - Method in class weka.gui.beans.SerializedModelSaver

Get the prefix to prepend to the model file names.

getPremise() - Method in class weka.associations.AssociationRule

Get the premise of this rule.

getPremise() - Method in class weka.associations.DefaultAssociationRule

getPremiseSupport() - Method in class weka.associations.AssociationRule

Get the support for the premise.

getPremiseSupport() - Method in class weka.associations.DefaultAssociationRule

getPreprocessing() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Gets the filter used for preprocessing

getPreprocessPanel() - Method in class weka.gui.explorer.Explorer

returns the instance of the PreprocessPanel being used in this instance of the Explorer

getPreserveInstancesOrder() - Method in class weka.clusterers.SimpleKMeans

Gets whether order of instances must be preserved.

getPreserveOrder() - Method in class weka.gui.beans.CrossValidationFoldMaker

Returns true if the order of the incoming instances is to be preserved under cross-validation (no randomization or stratification is done in this case).

getPrimaryMetricName() - Method in class weka.associations.AssociationRule

Get the name of the primary metric of this rule (e.g.

getPrimaryMetricName() - Method in class weka.associations.DefaultAssociationRule

getPrimaryMetricValue() - Method in class weka.associations.AssociationRule

Get the value of the metric for this rule.

getPrimaryMetricValue() - Method in class weka.associations.DefaultAssociationRule

getPrintColNames() - Method in class weka.experiment.ResultMatrix

returns whether column names or numbers instead are printed.

getPrintLeafModels() - Method in class weka.classifiers.trees.HoeffdingTree

getPrintNewick() - Method in class weka.clusterers.HierarchicalClusterer

getPrintRowNames() - Method in class weka.experiment.ResultMatrix

returns whether row names or numbers instead are printed.

getPrintTrees() - Method in class weka.classifiers.trees.RandomForest

Get whether to print the individual ensemble trees in the output

getPriorProbability() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the priorProbability property.

getPriorProbability(String) - Method in class weka.core.pmml.TargetMetaInfo

Get the prior probability for the supplied value.

getProbabilities() - Method in class weka.gui.boundaryvisualizer.RemoteResult

Return the probability distributions for this row in the visualization

getProbability(int, int, int) - Method in class weka.classifiers.bayes.BayesNet

get particular probability of the conditional probability distribtion of a node given its parents.

getProbability(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Get a probability estimate for a value

getProbability() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Gets the value of the probability property.

getProbability(double, double) - Method in interface weka.estimators.ConditionalEstimator

Get a probability for a value conditional on another value

getProbability(double, double) - Method in class weka.estimators.DDConditionalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.DiscreteEstimator

Get a probability estimate for a value

getProbability(double, double) - Method in class weka.estimators.DKConditionalEstimator

Get a probability estimate for a value

getProbability(double, double) - Method in class weka.estimators.DNConditionalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.Estimator

Get a probability estimate for a value.

getProbability(double, double) - Method in class weka.estimators.KDConditionalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.KernelEstimator

Get a probability estimate for a value.

getProbability(double, double) - Method in class weka.estimators.KKConditionalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.MahalanobisEstimator

Get a probability estimate for a value

getProbability(double[]) - Method in interface weka.estimators.MultivariateEstimator

Returns the probability density estimate at the given point.

getProbability(double[]) - Method in class weka.estimators.MultivariateGaussianEstimator

Returns the probability density estimate at the given point.

getProbability(double, double) - Method in class weka.estimators.NDConditionalEstimator

Get a probability estimate for a value

getProbability(double, double) - Method in class weka.estimators.NNConditionalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.NormalEstimator

Get a probability estimate for a value

getProbability(double) - Method in class weka.estimators.PoissonEstimator

Get a probability estimate for a value

getProducer() - Method in class weka.associations.AssociationRules

Get a string describing the scheme that produced these rules.

getProgressBar() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

Returns a handle to the progressBar of this LayoutEngine.

getProgressBar() - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method returns the progress bar for the LayoutEngine, which shows the progress of the layout process, if it takes a while to layout the graph

getProlog() - Method in class weka.core.OptionHandlerJavadoc

whether "Valid options are..." prolog is included in the Javadoc

getProlog() - Method in class weka.core.TechnicalInformationHandlerJavadoc

whether "Valid options are..." prolog is included in the Javadoc

getProperties() - Method in class weka.core.converters.DatabaseConnection

Returns the underlying properties object.

getProperties() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the associated properties file.

getProperties() - Static method in class weka.gui.explorer.ExplorerDefaults

returns the associated properties file.

getProperty() - Method in class weka.core.pmml.FieldMetaInfo.Value

getProperty() - Method in class weka.core.pmml.jaxbbindings.Value

Gets the value of the property property.

getPropertyArray() - Method in class weka.experiment.Experiment

Gets the array of values to set the custom property to.

getPropertyArrayLength() - Method in class weka.experiment.Experiment

Gets the number of custom iterator values that have been defined for the experiment.

getPropertyArrayValue(int) - Method in class weka.experiment.Experiment

Gets a specified value from the custom property iterator array.

getPropertyDescriptor(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath

returns the property associated with the given path, null if a problem occurred.

getPropertyDescriptor(Object, String) - Static method in class weka.core.PropertyPath

returns the property associated with the given path

getPropertyDescriptors() - Method in class weka.classifiers.misc.InputMappedClassifierBeanInfo

Get an array of PropertyDescriptors for the InputMappedClassifier's public properties.

getPropertyDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo

Returns the property descriptors

getPropertyDescriptors() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo

Get the property descriptors for this bean

getPropertyDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo

Returns the property descriptors

getPropertyDescriptors() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo

Return the property descriptors for this bean

getPropertyDescriptors() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo

Return the property descriptors for this bean

getPropertyDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo

Return the property descriptors for this bean

getPropertyDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo

Get the property descriptors for this bean

getPropertyDescriptors() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo

Get the property descriptors for this bean

getPropertyPath() - Method in class weka.experiment.Experiment

Gets the path of properties taken to get to the custom property to iterate over.

getPRow() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the pRow property.

getPruningMethod() - Method in class weka.classifiers.functions.supportVector.StringKernel

Gets the method used for pruning.

getPValue() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the pValue property.

getPValueAlpha() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the pValueAlpha property.

getPValueFinal() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the pValueFinal property.

getPValueInitial() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the pValueInitial property.

getQ() - Method in class weka.core.matrix.QRDecomposition

Generate and return the (economy-sized) orthogonal factor

getQuality() - Method in class weka.gui.visualize.JPEGWriter

returns the quality the JPEG will be stored in.

getQuantile() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the quantile property.

getQuantileLimit() - Method in class weka.core.pmml.jaxbbindings.Quantile

Gets the value of the quantileLimit property.

getQuantileValue() - Method in class weka.core.pmml.jaxbbindings.Quantile

Gets the value of the quantileValue property.

getQuery() - Method in class weka.core.converters.DatabaseLoader

Gets the query to execute against the database

getQuery() - Method in class weka.experiment.InstanceQuery

Get the query to execute against the database

getQuery() - Method in class weka.gui.sql.event.QueryExecuteEvent

returns the query that was executed

getQuery() - Method in class weka.gui.sql.event.ResultChangedEvent

returns the query that was executed

getQuery() - Method in class weka.gui.sql.QueryPanel

returns the currently displayed query.

getQuery() - Method in class weka.gui.sql.ResultSetTable

returns the query that produced the table model

getQuery() - Method in class weka.gui.sql.SqlViewer

returns the query from the currently active tab in the ResultPanel, otherwise an empty string.

getQuery() - Method in class weka.gui.sql.SqlViewerDialog

returns the chosen query, if any.

getQueryPanel() - Method in class weka.gui.sql.ResultPanel

returns the currently set QueryPanel, can be NULL

getQuoteDelimiters() - Method in class weka.gui.scripting.SyntaxDocument

Returns the quote delimiter characters to use.

getQuoteEscape() - Method in class weka.gui.scripting.SyntaxDocument

Returns the character for escaping a quote delimiter.

getR() - Method in class weka.core.matrix.QRDecomposition

Return the upper triangular factor

getRadius() - Method in class weka.core.neighboursearch.balltrees.BallNode

Returns the radius of the node's ball.

getRandom() - Method in class weka.datagenerators.DataGenerator

Gets the random generator.

getRandomizeData() - Method in class weka.experiment.ExplicitTestsetResultProducer

Get if dataset is to be randomized.

getRandomizeData() - Method in class weka.experiment.RandomSplitResultProducer

Get if dataset is to be randomized

getRandomLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the randomLiftGraph property.

getRandomNumberGenerator(long) - Method in class weka.core.Instances

Returns a random number generator.

getRandomOrder() - Method in class weka.classifiers.bayes.net.search.global.K2

Get random order flag

getRandomOrder() - Method in class weka.classifiers.bayes.net.search.local.K2

Get random order flag

getRandomSeed() - Method in class weka.classifiers.functions.SMO

Get the value of randomSeed.

getRandomSeed() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns the seed value of random number generator.

getRandomSeed() - Method in class weka.filters.supervised.instance.Resample

Gets the random number seed.

getRandomSeed() - Method in class weka.filters.supervised.instance.SpreadSubsample

Gets the random number seed.

getRandomSeed() - Method in class weka.filters.unsupervised.attribute.AddNoise

Gets the random number seed.

getRandomSeed() - Method in class weka.filters.unsupervised.instance.Randomize

Get the random number generator seed value.

getRandomSeed() - Method in class weka.filters.unsupervised.instance.Resample

Gets the random number seed.

getRandomSeed() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Gets the random number seed.

getRandomWidthFactor() - Method in class weka.classifiers.meta.MultiClassClassifier

Gets the multiplier when generating random codes.

getRange() - Method in class weka.core.InstanceComparator

Returns the attribute range to use in the comparison.

getRange(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets a single Range from the set of available Ranges.

getRanges() - Method in class weka.core.NormalizableDistance

Method to get the ranges.

getRanges() - Method in class weka.core.Range

Gets the string representing the selected range of values.

getRanges() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets the list of possible Ranges to choose from.

getRank() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the rank property.

getRankBasis() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the rankBasis property.

getRankingQuality() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the rankingQuality property.

getRankOrder() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the rankOrder property.

getRawOutput() - Method in class weka.experiment.CrossValidationResultProducer

Get if raw split evaluator output is to be saved

getRawOutput() - Method in class weka.experiment.ExplicitTestsetResultProducer

Get if raw split evaluator output is to be saved.

getRawOutput() - Method in class weka.experiment.RandomSplitResultProducer

Get if raw split evaluator output is to be saved

getRawResultOutput() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the raw output from the classifier

getRawResultOutput() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the raw output from the classifier

getRawResultOutput() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the raw output from the classifier

getRawResultOutput() - Method in interface weka.experiment.SplitEvaluator

Returns the raw output for the most recent call to getResult.

getReadable() - Method in class weka.core.Tag

Gets the string description of the Tag.

getReader(String, String) - Static method in class weka.gui.Loader

returns a Reader for the given filename and dir, can be NULL if it fails

getReader(String) - Method in class weka.gui.Loader

returns a Reader for the given filename, can be NULL if it fails

getReadIncrementally() - Method in class weka.gui.SetInstancesPanel

Gets whether instances are to be read incrementally or not.

getRealEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition

Return the real parts of the eigenvalues

getREALEntries() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Gets the value of the realEntries property.

getREALSparseArray() - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Gets the value of the realSparseArray property.

getReasonCode() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the reasonCode property.

getReasonCode() - Method in class weka.core.pmml.jaxbbindings.Characteristic

Gets the value of the reasonCode property.

getReasonCodeAlgorithm() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the reasonCodeAlgorithm property.

getRecall() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the recall.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Gets the value of the recordCount property.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.Node

Gets the value of the recordCount property.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the recordCount property.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Gets the value of the recordCount property.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the recordCount property.

getRecordCount() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the recordCount property.

getReducedErrorPruning() - Method in class weka.classifiers.rules.PART

Get the value of reducedErrorPruning.

getReducedErrorPruning() - Method in class weka.classifiers.trees.J48

Get the value of reducedErrorPruning.

getReduceNumberOfDistanceCalcsViaCanopies() - Method in class weka.clusterers.SimpleKMeans

Get whether to use canopies to reduce the number of distance computations required

getRefer() - Method in class weka.gui.treevisualizer.Node

Get the value of refer.

getReferencePoint() - Method in class weka.core.pmml.jaxbbindings.Parameter

Gets the value of the referencePoint property.

getRefreshFreq() - Method in class weka.gui.beans.StripChart

Get the refresh frequency

getRegex() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Get whether this is a regular expression match or not

getRegex() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Get whether this is a regular expression match or not

getRegOptimizer() - Method in class weka.classifiers.functions.SMOreg

returns the learning algorithm

getRegressionModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the regressionModel property.

getRegressionTable() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the regressionTable property.

getRegressionTree() - Method in class weka.classifiers.trees.m5.Rule

Get the value of regressionTree.

getRegressionTree() - Method in class weka.classifiers.trees.m5.RuleNode

Get the value of regressionTree.

getRelation() - Method in class weka.core.TestInstances

returns the current name of the relation

getRelationalClassFormat() - Method in class weka.core.TestInstances

returns the current strcuture of the relational class attribute, can be null

getRelationalFormat(int) - Method in class weka.core.TestInstances

returns the format for the specified relational attribute, can be null

getRelationFind() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the currently set regular expression to use on the relation name.

getRelationForTableName() - Method in class weka.core.converters.DatabaseSaver

Gets whether or not the relation name is used as name of the table.

getRelationName() - Method in class weka.datagenerators.DataGenerator

Gets the relation name the dataset should have.

getRelationNameForFilename() - Method in class weka.gui.beans.Saver

Get whether the relation name is the primary part of the filename.

getRelationReplace() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the currently set replacement string to use on the relation name.

getRemoteHosts() - Method in class weka.experiment.RemoteExperiment

Get the list of remote host names

getRemoveAllMissingCols() - Method in class weka.associations.Apriori

Returns whether columns containing all missing values are to be removed

getRemoveClassColumn() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Get whether the class column is to be removed.

getRemoveFilterClassnames() - Static method in class weka.gui.experiment.ExperimenterDefaults

whether the filter classnames in the dataset names are removed by default.

getRemoveFilterName() - Method in class weka.experiment.ResultMatrix

returns whether the filter classname is removed from the dataset name.

getRemoveOldClass() - Method in class weka.filters.supervised.attribute.AddClassification

Get whether the old class attribute is removed.

getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

getRenderingHint(RenderingHints.Key) - Method in class weka.gui.visualize.PostscriptGraphics

getRenderingHints() - Method in class weka.gui.visualize.PostscriptGraphics

getRepetitions() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the number of repetitions to use.

getReplace() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the regular expression to replace matching attribute names with.

getReplace() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Get the replace string

getReplaceAll() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns whether all occurrences are replaced or just the first one.

getReplaceMissingValues() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Gets the current setting for using ReplaceMissingValues filter

getRepositoryPackageInfo(String) - Static method in class weka.core.WekaPackageManager

Get meta data for the latest version of a package from the repository

getRepositoryPackageInfo(String, String) - Static method in class weka.core.WekaPackageManager

Get meta data for a specific version of a package from the repository

getRepositoryPackageVersions(String) - Static method in class weka.core.WekaPackageManager

Get the versions of the supplied package available on the server

getRepresentCopiesUsingWeights() - Method in class weka.classifiers.meta.Bagging

Get whether copies of instances are represented using weights rather than explicitly.

getRescaleConstant() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the rescaleConstant property.

getRescaleFactor() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the rescaleFactor property.

getReset() - Method in class weka.classifiers.functions.MultilayerPerceptron

getReset() - Method in class weka.gui.beans.ChartEvent

get the value of the reset flag

getResetIncrementalClassifier() - Method in class weka.gui.beans.Classifier

Get whether to reset (by calling buildClassifier()) an incremental classifier, and thus discarding any previously learned model, before processing the first instance in the incoming stream.

getResetValue() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the resetValue property.

getResolvedName() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the name of the attribute after substituting any environment variables

getResolvedType() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the type of the attribute after substituting any environment variables

getResolvedValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the value of the attribute after substituting any environment variables

getResult() - Method in class weka.core.json.Parser

Returns the JSON data structure.

getResult() - Method in class weka.core.mathematicalexpression.Parser

Returns the result of the evaluation.

getResult(double[]) - Method in class weka.core.pmml.BuiltInArithmetic

Get the result of applying this function.

getResult(double[]) - Method in class weka.core.pmml.BuiltInMath

Get the result of applying this function.

getResult(double[]) - Method in class weka.core.pmml.BuiltInString

Get the result of applying this function.

getResult(double[]) - Method in class weka.core.pmml.Constant

Get the result of evaluating the expression.

getResult(double[]) - Method in class weka.core.pmml.DefineFunction

Get the result of applying this function.

getResult(double[]) - Method in class weka.core.pmml.Discretize

Get the result of evaluating the expression.

getResult(double[]) - Method in class weka.core.pmml.Expression

Get the result of evaluating the expression.

getResult(double[]) - Method in class weka.core.pmml.FieldRef

getResult(double[]) - Method in class weka.core.pmml.Function

Get the result of applying this function.

getResult(double[]) - Method in class weka.core.pmml.NormContinuous

Get the result of evaluating the expression.

getResult(double[]) - Method in class weka.core.pmml.NormDiscrete

Get the result of evaluating the expression.

getResult(Instances, Instances) - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the results for the supplied train and test datasets.

getResult(Instances, Instances) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Gets the results for the supplied train and test datasets.

getResult(Instances, Instances) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the results for the supplied train and test datasets.

getResult(Instances, Instances) - Method in class weka.experiment.RegressionSplitEvaluator

Gets the results for the supplied train and test datasets.

getResult(Instances, Instances) - Method in interface weka.experiment.SplitEvaluator

Gets the results for the supplied train and test datasets.

getResult() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Returns the result of the evaluation.

getResult() - Method in class weka.gui.experiment.OutputFormatDialog

the result from the last display of the dialog, the same is returned from showDialog.

getResultCategorical(double[]) - Method in class weka.core.pmml.Constant

Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.

getResultCategorical(double[]) - Method in class weka.core.pmml.Discretize

Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.

getResultCategorical(double[]) - Method in class weka.core.pmml.Expression

Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.

getResultCategorical(double[]) - Method in class weka.core.pmml.FieldRef

getResultCategorical(double[]) - Method in class weka.core.pmml.NormContinuous

Always throws an Exception since the result of NormContinuous must be continuous.

getResultCategorical(double[]) - Method in class weka.core.pmml.NormDiscrete

Always throws an Exception since the result of NormDiscrete must be continuous.

getResultContinuous(double[]) - Method in class weka.core.pmml.Expression

Get the result of evaluating the expression for continuous optype.

getResultField() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the resultField property.

getResultField() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the resultField property.

getResultFromTable(String, ResultProducer, Object[]) - Method in class weka.experiment.DatabaseUtils

Executes a database query to extract a result for the supplied key from the database.

getResultInverse(double[]) - Method in class weka.core.pmml.NormContinuous

Compute the inverse of the normalization (i.e.

getResultListener() - Method in class weka.experiment.Experiment

Gets the result listener where results will be sent.

getResultMatrix() - Method in class weka.experiment.PairedTTester

Gets the instance that produces the output.

getResultMatrix() - Method in interface weka.experiment.Tester

Gets the instance that produces the output.

getResultMatrix() - Method in class weka.gui.experiment.OutputFormatDialog

Gets the currently selected output format result matrix.

getResultNames() - Method in class weka.experiment.AveragingResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the names of each of the result columns produced for a single run.

getResultNames() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Gets the names of each of the result columns produced for a single run.

getResultNames() - Method in class weka.experiment.CrossValidationResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.DatabaseResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the names of each of the result columns produced for a single run.

getResultNames() - Method in class weka.experiment.ExplicitTestsetResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.LearningRateResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.RandomSplitResultProducer

Gets the names of each of the columns produced for a single run.

getResultNames() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the names of each of the result columns produced for a single run.

getResultNames() - Method in interface weka.experiment.ResultProducer

Gets the names of each of the result columns produced for a single run.

getResultNames() - Method in interface weka.experiment.SplitEvaluator

Gets the names of each of the result columns produced for a single run.

getResultProducer() - Method in class weka.experiment.AveragingResultProducer

Get the ResultProducer.

getResultProducer() - Method in class weka.experiment.DatabaseResultProducer

Get the ResultProducer.

getResultProducer() - Method in class weka.experiment.Experiment

Get the result producer used for the current experiment.

getResultProducer() - Method in class weka.experiment.LearningRateResultProducer

Get the ResultProducer.

getResultSet() - Method in class weka.experiment.DatabaseUtils

Gets the results generated by a previous query.

getResultSet() - Method in class weka.gui.sql.event.QueryExecuteEvent

returns the resultset that was produced, can be null in case the query failed

getResultSet() - Method in class weka.gui.sql.ResultSetHelper

the underlying resultset.

getResultsetKeyColumns() - Method in class weka.experiment.PairedTTester

Get the value of ResultsetKeyColumns.

getResultsetKeyColumns() - Method in interface weka.experiment.Tester

Get the value of ResultsetKeyColumns.

getResultsetName(int) - Method in class weka.experiment.PairedTTester

Gets a string descriptive of the specified resultset.

getResultsetName(int) - Method in interface weka.experiment.Tester

Gets a string descriptive of the specified resultset.

getResultsTableName(ResultProducer) - Method in class weka.experiment.DatabaseUtils

Gets the name of the experiment table that stores results from a particular ResultProducer.

getResultTypes() - Method in class weka.experiment.AveragingResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.ClassifierSplitEvaluator

Gets the data types of each of the result columns produced for a single run.

getResultTypes() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Gets the data types of each of the result columns produced for a single run.

getResultTypes() - Method in class weka.experiment.CrossValidationResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.DatabaseResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Gets the data types of each of the result columns produced for a single run.

getResultTypes() - Method in class weka.experiment.ExplicitTestsetResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.LearningRateResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.RandomSplitResultProducer

Gets the data types of each of the columns produced for a single run.

getResultTypes() - Method in class weka.experiment.RegressionSplitEvaluator

Gets the data types of each of the result columns produced for a single run.

getResultTypes() - Method in interface weka.experiment.ResultProducer

Gets the data types of each of the result columns produced for a single run.

getResultTypes() - Method in interface weka.experiment.SplitEvaluator

Gets the data types of each of the result columns produced for a single run.

getReturnValue() - Method in class weka.gui.DatabaseConnectionDialog

Returns which of OK or cancel was clicked from dialog

getReturnValue() - Method in class weka.gui.sql.SqlViewerDialog

returns whether the user clicked OK (JOptionPane.OK_OPTION) or whether he cancelled the dialog (JOptionPane.CANCEL_OPTION).

getRevision() - Method in class weka.associations.AbstractAssociator

Returns the revision string.

getRevision() - Method in class weka.associations.Apriori

Returns the revision string.

getRevision() - Method in class weka.associations.AprioriItemSet

Returns the revision string.

getRevision() - Method in class weka.associations.AssociatorEvaluation

Returns the revision string.

getRevision() - Method in class weka.associations.CheckAssociator

Returns the revision string.

getRevision() - Method in class weka.associations.FilteredAssociator

Returns the revision string.

getRevision() - Method in class weka.associations.FPGrowth

Returns the revision string.

getRevision() - Method in class weka.associations.ItemSet

Returns the revision string.

getRevision() - Method in class weka.associations.LabeledItemSet

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.ASEvaluation

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.ASSearch

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.AttributeSelection

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.BestFirst

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.BestFirst.Link2

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.BestFirst.LinkedList2

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.CfsSubsetEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.CheckAttributeSelection

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.CorrelationAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.GainRatioAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.GreedyStepwise

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.OneRAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.PrincipalComponents

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.Ranker

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns the revision string.

getRevision() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns the revision string.

getRevision() - Method in class weka.classifiers.AbstractClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.BayesNet

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.NaiveBayes

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.ADNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.BIFReader

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.EditableBayesNet

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.ParentSet

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.K2

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.global.TAN

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.K2

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.local.TAN

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.bayes.net.VaryNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.BVDecompose

Returns the revision string.

getRevision() - Method in class weka.classifiers.BVDecomposeSegCVSub

Returns the revision string.

getRevision() - Method in class weka.classifiers.CheckClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.CheckSource

Returns the revision string.

getRevision() - Method in class weka.classifiers.CostMatrix

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.ConfusionMatrix

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.CostCurve

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.Evaluation

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.EvaluationUtils

Returns the revision string.

getRevision() - Method in class weka.classifiers.Evaluation

getRevision() - Method in class weka.classifiers.evaluation.MarginCurve

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.NominalPrediction

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.NumericPrediction

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.RegressionAnalysis

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.ThresholdCurve

Returns the revision string.

getRevision() - Method in class weka.classifiers.evaluation.TwoClassStats

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.LinearRegression

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.Logistic

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.MultilayerPerceptron

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.neural.LinearUnit

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.neural.NeuralNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.neural.SigmoidUnit

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SGD

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SGDText

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SimpleLogistic

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SMO.BinarySMO

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SMO

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SMOreg

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.CheckKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.Puk

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.RegSMO

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.SMOset

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.VotedPerceptron

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.IBk

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.KStar

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache.TableEntry

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.kstar.KStarWrapper

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.LWL

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AdaBoostM1

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AdditiveRegression

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.Bagging

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.ClassificationViaRegression

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.CVParameterSelection

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.FilteredClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.LogitBoost

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.MultiClassClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.MultiScheme

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.RandomCommittee

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.RandomSubSpace

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.Stacking

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.Vote

Returns the revision string.

getRevision() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.misc.SerializedClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.pmml.consumer.GeneralRegression

getRevision() - Method in class weka.classifiers.pmml.consumer.NeuralNetwork

getRevision() - Method in class weka.classifiers.pmml.consumer.Regression

getRevision() - Method in class weka.classifiers.pmml.consumer.RuleSetModel

Get the revision string for this class

getRevision() - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel

getRevision() - Method in class weka.classifiers.pmml.consumer.TreeModel

getRevision() - Method in class weka.classifiers.rules.DecisionTable

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.DecisionTableHashKey

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.JRip.Antd

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.JRip

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.JRip.NominalAntd

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.JRip.NumericAntd

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.JRip.RipperRule

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.M5Rules

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.OneR

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.part.C45PruneableDecList

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.part.ClassifierDecList

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.PART

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.part.MakeDecList

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.part.PruneableDecList

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.RuleStats

Returns the revision string.

getRevision() - Method in class weka.classifiers.rules.ZeroR

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.DecisionStump

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.BinC45Split

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.C45ModelSelection

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.C45Split

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.Distribution

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.EntropySplitCrit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.J48

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.NBTreeSplit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.NoSplit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.j48.Stats

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.LMT

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.lmt.LogisticBase

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.lmt.ResidualSplit

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.Impurity

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.Rule

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.RuleNode

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.Values

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.M5P

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.RandomForest

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.REPTree

Returns the revision string.

getRevision() - Method in class weka.classifiers.xml.XMLClassifier

Returns the revision string.

getRevision() - Method in class weka.clusterers.AbstractClusterer

Returns the revision string.

getRevision() - Method in class weka.clusterers.CheckClusterer

Returns the revision string.

getRevision() - Method in class weka.clusterers.ClusterEvaluation

Returns the revision string.

getRevision() - Method in class weka.clusterers.Cobweb.CNode

Returns the revision string.

getRevision() - Method in class weka.clusterers.Cobweb

Returns the revision string.

getRevision() - Method in class weka.clusterers.EM

Returns the revision string.

getRevision() - Method in class weka.clusterers.FarthestFirst

Returns the revision string.

getRevision() - Method in class weka.clusterers.FilteredClusterer

Returns the revision string.

getRevision() - Method in class weka.clusterers.HierarchicalClusterer

Returns the revision string.

getRevision() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns the revision string.

getRevision() - Method in class weka.clusterers.SimpleKMeans

Returns the revision string.

getRevision() - Method in class weka.core.AbstractInstance

Returns the revision string.

getRevision() - Method in class weka.core.AlgVector

Returns the revision string.

getRevision() - Method in class weka.core.AllJavadoc

Returns the revision string.

getRevision() - Method in class weka.core.Attribute

Returns the revision string.

getRevision() - Method in class weka.core.AttributeExpression

Returns the revision string.

getRevision() - Method in class weka.core.AttributeLocator

Returns the revision string.

getRevision() - Method in class weka.core.AttributeStats

Returns the revision string.

getRevision() - Method in class weka.core.BinarySparseInstance

Returns the revision string.

getRevision() - Method in class weka.core.Capabilities

Returns the revision string.

getRevision() - Method in class weka.core.ChebyshevDistance

Returns the revision string.

getRevision() - Method in class weka.core.CheckGOE

Returns the revision string.

getRevision() - Method in class weka.core.CheckOptionHandler

Returns the revision string.

getRevision() - Method in class weka.core.CheckScheme.PostProcessor

Returns the revision string.

getRevision() - Method in class weka.core.ClassCache

Returns the revision string.

getRevision() - Method in class weka.core.ClassDiscovery

Returns the revision string.

getRevision() - Method in class weka.core.ClassDiscovery.StringCompare

Returns the revision string.

getRevision() - Method in class weka.core.ClassloaderUtil

Returns the revision string.

getRevision() - Method in class weka.core.ContingencyTables

Returns the revision string.

getRevision() - Method in class weka.core.converters.ArffLoader.ArffReader

Returns the revision string.

getRevision() - Method in class weka.core.converters.ArffLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.ArffSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.C45Loader

Returns the revision string.

getRevision() - Method in class weka.core.converters.C45Saver

Returns the revision string.

getRevision() - Method in class weka.core.converters.ConverterUtils.DataSink

Returns the revision string.

getRevision() - Method in class weka.core.converters.ConverterUtils.DataSource

Returns the revision string.

getRevision() - Method in class weka.core.converters.ConverterUtils

Returns the revision string.

getRevision() - Method in class weka.core.converters.CSVLoader

getRevision() - Method in class weka.core.converters.CSVSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.DatabaseConnection

Returns the revision string.

getRevision() - Method in class weka.core.converters.DatabaseLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.DatabaseSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.JSONLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.JSONSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.LibSVMLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.LibSVMSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.MatlabLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.MatlabSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.SerializedInstancesLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.SerializedInstancesSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.StreamTokenizerUtils

getRevision() - Method in class weka.core.converters.SVMLightLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.SVMLightSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.TextDirectoryLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.XRFFLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.XRFFSaver

Returns the revision string.

getRevision() - Method in class weka.core.Debug.Clock

Returns the revision string.

getRevision() - Method in class weka.core.Debug.DBO

Returns the revision string.

getRevision() - Method in class weka.core.Debug

Returns the revision string.

getRevision() - Method in class weka.core.Debug.Log

Returns the revision string.

getRevision() - Method in class weka.core.Debug.Random

Returns the revision string.

getRevision() - Method in class weka.core.Debug.SimpleLog

Returns the revision string.

getRevision() - Method in class weka.core.Debug.Timestamp

Returns the revision string.

getRevision() - Method in class weka.core.DenseInstance

Returns the revision string.

getRevision() - Method in class weka.core.Environment

Returns the revision string.

getRevision() - Method in class weka.core.EuclideanDistance

Returns the revision string.

getRevision() - Method in class weka.core.FastVector

Deprecated. Returns the revision string.

getRevision() - Method in class weka.core.FindWithCapabilities

Returns the revision string.

getRevision() - Method in class weka.core.GlobalInfoJavadoc

Returns the revision string.

getRevision() - Method in class weka.core.InstanceComparator

Returns the revision string.

getRevision() - Method in class weka.core.Instances

Returns the revision string.

getRevision() - Method in class weka.core.ListOptions

Returns the revision string.

getRevision() - Method in class weka.core.logging.ConsoleLogger

Returns the revision string.

getRevision() - Method in class weka.core.logging.FileLogger

Returns the revision string.

getRevision() - Method in class weka.core.logging.OutputLogger

Returns the revision string.

getRevision() - Method in class weka.core.ManhattanDistance

Returns the revision string.

getRevision() - Method in class weka.core.MathematicalExpression

Returns the revision string.

getRevision() - Method in class weka.core.matrix.CholeskyDecomposition

Returns the revision string.

getRevision() - Method in class weka.core.matrix.DoubleVector

Returns the revision string.

getRevision() - Method in class weka.core.matrix.EigenvalueDecomposition

Returns the revision string.

getRevision() - Method in class weka.core.matrix.ExponentialFormat

Returns the revision string.

getRevision() - Method in class weka.core.matrix.FlexibleDecimalFormat

Returns the revision string.

getRevision() - Method in class weka.core.matrix.FloatingPointFormat

Returns the revision string.

getRevision() - Method in class weka.core.Matrix

Deprecated. Returns the revision string.

getRevision() - Method in class weka.core.matrix.IntVector

Returns the revision string.

getRevision() - Method in class weka.core.matrix.LinearRegression

Returns the revision string.

getRevision() - Method in class weka.core.matrix.LUDecomposition

Returns the revision string.

getRevision() - Method in class weka.core.matrix.Maths

Returns the revision string.

getRevision() - Method in class weka.core.matrix.Matrix

Returns the revision string.

getRevision() - Method in class weka.core.matrix.QRDecomposition

Returns the revision string.

getRevision() - Method in class weka.core.matrix.SingularValueDecomposition

Returns the revision string.

getRevision() - Method in class weka.core.Memory

Returns the revision string.

getRevision() - Method in class weka.core.MinkowskiDistance

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.BallTree

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.BallNode

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.CoverTree

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.covertrees.Stack

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.KDTree

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.LinearNNSearch

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the revision string.

getRevision() - Method in class weka.core.Option

Returns the revision string.

getRevision() - Method in class weka.core.OptionHandlerJavadoc

Returns the revision string.

getRevision() - Method in class weka.core.PropertyPath

Returns the revision string.

getRevision() - Method in class weka.core.PropertyPath.Path

Returns the revision string.

getRevision() - Method in class weka.core.PropertyPath.PathElement

Returns the revision string.

getRevision() - Method in class weka.core.ProtectedProperties

Returns the revision string.

getRevision() - Method in class weka.core.Queue

Returns the revision string.

getRevision() - Method in class weka.core.RandomVariates

Returns the revision string.

getRevision() - Method in class weka.core.Range

Returns the revision string.

getRevision() - Method in class weka.core.RelationalLocator

Returns the revision string.

getRevision() - Method in interface weka.core.RevisionHandler

Returns the revision string.

getRevision() - Method in class weka.core.scripting.Groovy

Returns the revision string.

getRevision() - Method in class weka.core.scripting.Jython

Returns the revision string.

getRevision() - Method in class weka.core.SelectedTag

Returns the revision string.

getRevision() - Method in class weka.core.SerializationHelper

Returns the revision string.

getRevision() - Method in class weka.core.SerializedObject

Returns the revision string.

getRevision() - Method in class weka.core.SingleIndex

Returns the revision string.

getRevision() - Method in class weka.core.SparseInstance

Returns the revision string.

getRevision() - Method in class weka.core.SpecialFunctions

Returns the revision string.

getRevision() - Method in class weka.core.Statistics

Returns the revision string.

getRevision() - Method in class weka.core.stemmers.IteratedLovinsStemmer

Returns the revision string.

getRevision() - Method in class weka.core.stemmers.LovinsStemmer

Returns the revision string.

getRevision() - Method in class weka.core.stemmers.NullStemmer

Returns the revision string.

getRevision() - Method in class weka.core.stemmers.SnowballStemmer

Returns the revision string.

getRevision() - Method in class weka.core.stemmers.Stemming

Returns the revision string.

getRevision() - Method in class weka.core.Stopwords

Returns the revision string.

getRevision() - Method in class weka.core.StringLocator

Returns the revision string.

getRevision() - Method in class weka.core.SystemInfo

Returns the revision string.

getRevision() - Method in class weka.core.Tag

Returns the revision string.

getRevision() - Method in class weka.core.TechnicalInformation

Returns the revision string.

getRevision() - Method in class weka.core.TechnicalInformationHandlerJavadoc

Returns the revision string.

getRevision() - Method in class weka.core.Tee

Returns the revision string.

getRevision() - Method in class weka.core.TestInstances

Returns the revision string.

getRevision() - Method in class weka.core.tokenizers.AlphabeticTokenizer

Returns the revision string.

getRevision() - Method in class weka.core.tokenizers.NGramTokenizer

Returns the revision string.

getRevision() - Method in class weka.core.tokenizers.WordTokenizer

Returns the revision string.

getRevision() - Method in class weka.core.Trie

Returns the revision string.

getRevision() - Method in class weka.core.Trie.TrieIterator

Returns the revision string.

getRevision() - Method in class weka.core.Trie.TrieNode

Returns the revision string.

getRevision() - Method in class weka.core.Utils

Returns the revision string.

getRevision() - Method in class weka.core.Version

Returns the revision string.

getRevision() - Method in class weka.core.WekaEnumeration

Returns the revision string.

getRevision() - Method in class weka.core.xml.KOML

Returns the revision string.

getRevision() - Method in class weka.core.xml.MethodHandler

Returns the revision string.

getRevision() - Method in class weka.core.xml.PropertyHandler

Returns the revision string.

getRevision() - Method in class weka.core.xml.SerialUIDChanger

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLBasicSerialization

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLDocument

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLInstances

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLOptions

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLSerialization

Returns the revision string.

getRevision() - Method in class weka.core.xml.XMLSerializationMethodHandler

Returns the revision string.

getRevision() - Method in class weka.core.xml.XStream

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.classification.LED24

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.regression.Expression

Returns the revision string.

getRevision() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns the revision string.

getRevision() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the revision string.

getRevision() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns the revision string.

getRevision() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns the revision string.

getRevision() - Method in class weka.datagenerators.Test

Returns the revision string.

getRevision() - Method in class weka.estimators.CheckEstimator.AttrTypes

Returns the revision string.

getRevision() - Method in class weka.estimators.CheckEstimator.EstTypes

Returns the revision string.

getRevision() - Method in class weka.estimators.CheckEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.CheckEstimator.PostProcessor

Returns the revision string.

getRevision() - Method in class weka.estimators.DDConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.DiscreteEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.DKConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.DNConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.Estimator

Returns the revision string.

getRevision() - Method in class weka.estimators.EstimatorUtils

Returns the revision string.

getRevision() - Method in class weka.estimators.KDConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.KernelEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.KKConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.MahalanobisEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.NDConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.NNConditionalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.NormalEstimator

Returns the revision string.

getRevision() - Method in class weka.estimators.PoissonEstimator

Returns the revision string.

getRevision() - Method in class weka.experiment.AveragingResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.ClassifierSplitEvaluator

Returns the revision string.

getRevision() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns the revision string.

getRevision() - Method in class weka.experiment.CrossValidationResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.CrossValidationSplitResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.CSVResultListener

Returns the revision string.

getRevision() - Method in class weka.experiment.DatabaseResultListener

Returns the revision string.

getRevision() - Method in class weka.experiment.DatabaseResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.DatabaseUtils

Returns the revision string.

getRevision() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns the revision string.

getRevision() - Method in class weka.experiment.Experiment

Returns the revision string.

getRevision() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.InstanceQuery

Returns the revision string.

getRevision() - Method in class weka.experiment.InstancesResultListener

Returns the revision string.

getRevision() - Method in class weka.experiment.LearningRateResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.OutputZipper

Returns the revision string.

getRevision() - Method in class weka.experiment.PairedCorrectedTTester

Returns the revision string.

getRevision() - Method in class weka.experiment.PairedStats

Returns the revision string.

getRevision() - Method in class weka.experiment.PairedStatsCorrected

Returns the revision string.

getRevision() - Method in class weka.experiment.PairedTTester

Returns the revision string.

getRevision() - Method in class weka.experiment.PropertyNode

Returns the revision string.

getRevision() - Method in class weka.experiment.RandomSplitResultProducer

Returns the revision string.

getRevision() - Method in class weka.experiment.RegressionSplitEvaluator

Returns the revision string.

getRevision() - Method in class weka.experiment.RemoteEngine

Returns the revision string.

getRevision() - Method in class weka.experiment.RemoteExperiment

Returns the revision string.

getRevision() - Method in class weka.experiment.RemoteExperimentSubTask

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixCSV

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixGnuPlot

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixHTML

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixLatex

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixPlainText

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixSignificance

Returns the revision string.

getRevision() - Method in class weka.experiment.Stats

Returns the revision string.

getRevision() - Method in class weka.experiment.TaskStatusInfo

Returns the revision string.

getRevision() - Method in class weka.experiment.xml.XMLExperiment

Returns the revision string.

getRevision() - Method in class weka.filters.AllFilter

Returns the revision string.

getRevision() - Method in class weka.filters.CheckSource

Returns the revision string.

getRevision() - Method in class weka.filters.Filter

Returns the revision string.

getRevision() - Method in class weka.filters.MultiFilter

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.AttributeSelection

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.ClassOrder

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.Discretize

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.NominalToBinary

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.PartitionMembership

getRevision() - Method in class weka.filters.supervised.instance.Resample

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Add

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AddID

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Center

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Copy

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Discretize

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NominalToString

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NumericToBinary

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Obfuscate

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Remove

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Reorder

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Standardize

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SwapValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Transpose

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.Randomize

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.Resample

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Returns the revision string.

getRevision() - Method in class weka.gui.beans.FlowRunner

getRevision() - Method in class weka.gui.sql.DbUtils

Returns the revision string.

getRidge() - Method in class weka.classifiers.functions.LinearRegression

Get the value of Ridge.

getRidge() - Method in class weka.classifiers.functions.Logistic

Gets the ridge in the log-likelihood.

getRightMargin() - Method in class weka.core.pmml.jaxbbindings.Interval

Gets the value of the rightMargin property.

getRMSE() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the rmse property.

getROC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the roc property.

getROCArea(Instances) - Static method in class weka.classifiers.evaluation.ThresholdCurve

Calculates the area under the ROC curve as the Wilcoxon-Mann-Whitney statistic.

getROCGraph() - Method in class weka.core.pmml.jaxbbindings.ROC

Gets the value of the rocGraph property.

getROCString() - Method in class weka.gui.visualize.ThresholdVisualizePanel

This extracts the ROC area string

getRoot() - Method in class weka.core.Trie

returns the root node of the trie

getRoot() - Method in class weka.gui.treevisualizer.Node

Get the value of root.

getRootMeanSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the rootMeanSquaredError property.

getRootNode() - Method in class weka.core.xml.XMLDocument

returns the current root node.

getRow(int) - Method in class weka.core.Matrix

Deprecated. Gets a row of the matrix and returns it as double array.

getRow() - Method in class weka.core.pmml.jaxbbindings.InlineTable

Gets the value of the row property.

getRow() - Method in class weka.core.pmml.jaxbbindings.MatCell

Gets the value of the row property.

getRow() - Static method in class weka.gui.experiment.ExperimenterDefaults

the comma-separated list of attribute names that identify a row.

getRowCount() - Method in class weka.experiment.ResultMatrix

returns the number of rows.

getRowCount() - Method in class weka.gui.arffviewer.ArffTableModel

returns the number of rows in the model

getRowCount() - Method in class weka.gui.beans.InteractiveTableModel

getRowCount() - Method in class weka.gui.SortedTableModel

Returns the number of rows in the model.

getRowCount() - Method in class weka.gui.sql.ResultSetHelper

returns the number of rows in the resultset.

getRowCount() - Method in class weka.gui.sql.ResultSetTableModel

returns the number of rows in the model.

getRowDimension() - Method in class weka.core.matrix.Matrix

Get row dimension.

getRowHidden(int) - Method in class weka.experiment.ResultMatrix

returns the hidden status of the row, if the index is valid, otherwise false.

getRowName(int) - Method in class weka.experiment.ResultMatrix

returns the name of the row, if the index is valid, otherwise null.

getRowNameWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the row names.

getRowOrder() - Method in class weka.experiment.ResultMatrix

returns the current order of the rows, null means the default order.

getRowPackedCopy() - Method in class weka.core.matrix.Matrix

Make a one-dimensional row packed copy of the internal array.

getRsource() - Method in class weka.gui.treevisualizer.Edge

Get the value of rsource.

getRSquared() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the rSquared property.

getRtarget() - Method in class weka.gui.treevisualizer.Edge

Get the value of rtarget.

getRule() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the rule property.

getRule() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the rule property.

getRuleFeature() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the ruleFeature property.

getRuleMetricNames() - Method in class weka.associations.Apriori

Gets a list of the names of the metrics output for each rule.

getRuleMetricNames() - Method in interface weka.associations.AssociationRulesProducer

Gets a list of the names of the metrics output for each rule.

getRuleMetricNames() - Method in class weka.associations.FilteredAssociator

Gets a list of the names of the metrics output for each rule.

getRuleMetricNames() - Method in class weka.associations.FPGrowth

Gets a list of the names of the metrics output for each rule.

getRules() - Method in class weka.associations.AssociationRules

Get the rules.

getRules() - Method in class weka.associations.FilteredAssociationRules

Get the rules.

getRules() - Method in class weka.gui.beans.BatchAssociationRulesEvent

Get the encapsulated association rules.

getRuleSelectionMethod() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the ruleSelectionMethod property.

getRuleset() - Method in class weka.classifiers.rules.JRip

Get the ruleset generated by Ripper

getRuleset() - Method in class weka.classifiers.rules.RuleStats

Get the ruleset of the stats

getRuleSetModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the ruleSetModel property.

getRulesetSize() - Method in class weka.classifiers.rules.RuleStats

Get the size of the ruleset in the stats

getRulesMustContain() - Method in class weka.associations.FPGrowth

Get the comma separated list of items that rules must contain in order to be output.

getRuleStats(int) - Method in class weka.classifiers.rules.JRip

Get the statistics of the ruleset in the given position

getRunColumn() - Method in class weka.experiment.PairedTTester

Get the value of RunColumn.

getRunColumn() - Method in interface weka.experiment.Tester

Get the value of RunColumn.

getRunLower() - Method in class weka.experiment.Experiment

Get the lower run number for the experiment.

getRunNumber() - Method in class weka.gui.beans.BatchClassifierEvent

Get the run number.

getRunNumber() - Method in class weka.gui.beans.TestSetEvent

Get the run number that this training set belongs to.

getRunNumber() - Method in class weka.gui.beans.TrainingSetEvent

Get the run number that this training set belongs to.

getRuns() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getRuns() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Returns the number of runs

getRuns() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

getRuns() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

getRuns() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getRuns() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

getRuns() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

getRuns() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

getRunUpper() - Method in class weka.experiment.Experiment

Get the upper run number for the experiment.

getS() - Method in class weka.core.matrix.SingularValueDecomposition

Return the diagonal matrix of singular values

getSample() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE

Gets the value of the sample property.

getSampleSize() - Method in class weka.attributeSelection.ReliefFAttributeEval

Get the number of instances used for estimating attributes

getSampleSize() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Gets the subsample size.

getSampleSizePercent() - Method in class weka.filters.supervised.instance.Resample

Gets the subsample size as a percentage of the original set.

getSampleSizePercent() - Method in class weka.filters.unsupervised.instance.Resample

Gets the subsample size as a percentage of the original set.

getSaveDialogTitle() - Method in class weka.gui.visualize.PrintableComponent

returns the title for the save dialog.

getSaveDialogTitle() - Method in interface weka.gui.visualize.PrintableHandler

returns the title for the save dialog

getSaveDialogTitle() - Method in class weka.gui.visualize.PrintablePanel

returns the title for the save dialog

getSaveForVisualization() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Returns whether the instances are saved for visualization for only evaluation of the prediction is to happen.

getSaveInstanceData() - Method in class weka.classifiers.trees.J48

Check whether instance data is to be saved.

getSaveInstanceData() - Method in class weka.clusterers.Cobweb

Get the value of saveInstances.

getSaveInstances() - Method in class weka.classifiers.trees.M5P

Get whether instance data is being save.

getSaver() - Method in class weka.gui.ConverterFileChooser

returns the saver that was chosen by the user, can be null in case the user aborted the dialog or the open dialog was shown.

getSaverForExtension(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the saver to use for this kind of extension, returns null if none can be found.

getSaverForFile(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the saver to use for this kind of file, returns null if none can be found.

getSaverForFile(File) - Static method in class weka.core.converters.ConverterUtils

tries to determine the saver to use for this kind of file, returns null if none can be found.

getSaverTemplate() - Method in class weka.gui.beans.Saver

Get the saver

getScale() - Method in class weka.filters.unsupervised.attribute.Normalize

Get the scaling factor.

getScaleWidthToFit() - Method in class weka.gui.DocumentPrinting

Returns whether the width is to be scaled.

getScalingEnabled() - Method in class weka.gui.visualize.JComponentWriter

whether scaling is enabled or ignored

getScore() - Method in class weka.core.pmml.jaxbbindings.Node

Gets the value of the score property.

getScore() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the score property.

getScorecard() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the scorecard property.

getScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.RuleSet

Gets the value of the scoreDistribution property.

getScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the scoreDistribution property.

getScoreType() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

get quality measure to be used in searching for networks.

getScript() - Method in class weka.gui.scripting.event.ScriptExecutionEvent

Returns the script that triggered the event.

getScrollableTracksViewportHeight() - Method in class weka.gui.ETable

Changes the behavior of a table in a JScrollPane to be more like the behavior of JList, which expands to fill the available space.

getSearch() - Method in class weka.attributeSelection.CheckAttributeSelection

Get the current search method

getSearch() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Gets the search method used

getSearch() - Method in class weka.classifiers.rules.DecisionTable

Gets the current search method

getSearch() - Method in class weka.filters.supervised.attribute.AttributeSelection

Get the name of the search method

getSearchAlgorithm() - Method in class weka.classifiers.bayes.BayesNet

Get the SearchAlgorithm used as the search algorithm

getSearchBackwards() - Method in class weka.attributeSelection.GreedyStepwise

Get whether to search backwards

getSearchString() - Method in class weka.gui.arffviewer.ArffTable

returns the search string, can be NULL if no search string is set

getSearchTermination() - Method in class weka.attributeSelection.BestFirst

Get the termination criterion (number of non-improving nodes).

getSeasonalityExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the seasonalityExpoSmooth property.

getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Get the index of the second value used.

getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues

Get the index of the second value used.

getSeed() - Method in class weka.attributeSelection.OneRAttributeEval

Get the random number seed

getSeed() - Method in class weka.attributeSelection.ReliefFAttributeEval

Get the seed used for randomly sampling instances.

getSeed() - Method in class weka.attributeSelection.WrapperSubsetEval

Get the random number seed used for cross validation

getSeed() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getSeed() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Returns the random seed

getSeed() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

getSeed() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getSeed() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

getSeed() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

getSeed() - Method in class weka.classifiers.BVDecompose

Gets the random number seed

getSeed() - Method in class weka.classifiers.BVDecomposeSegCVSub

Gets the random number seed

getSeed() - Method in class weka.classifiers.evaluation.EvaluationUtils

Gets the seed for randomization during cross-validation

getSeed() - Method in class weka.classifiers.functions.MultilayerPerceptron

getSeed() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Gets the current seed value for the random number generator

getSeed() - Method in class weka.classifiers.functions.VotedPerceptron

Get the value of Seed.

getSeed() - Method in class weka.classifiers.meta.MultiScheme

Gets the random number seed.

getSeed() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableClassifier

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.rules.JRip

Gets the current seed value to use in randomizing the data

getSeed() - Method in class weka.classifiers.rules.PART

Get the value of Seed.

getSeed() - Method in class weka.classifiers.trees.J48

Get the value of Seed.

getSeed() - Method in class weka.classifiers.trees.RandomForest

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.trees.RandomTree

Gets the seed for the random number generations

getSeed() - Method in class weka.classifiers.trees.REPTree

Get the value of Seed.

getSeed() - Method in class weka.clusterers.RandomizableClusterer

Gets the seed for the random number generations

getSeed() - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Gets the seed for the random number generations

getSeed() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Gets the seed for the random number generations

getSeed() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns the seed for random number generator.

getSeed() - Method in interface weka.core.Randomizable

Gets the seed for the random number generations

getSeed() - Method in class weka.core.TestInstances

returns the current seed value

getSeed() - Method in class weka.datagenerators.DataGenerator

Gets the random number seed.

getSeed() - Method in class weka.filters.supervised.attribute.ClassOrder

Get the current randomization seed

getSeed() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets the random number seed used for shuffling the dataset.

getSeed() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Gets the random seed of the random number generator

getSeed() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Get the seed value for the random number generator.

getSeed() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets the random number seed used for shuffling the dataset.

getSeed() - Method in class weka.gui.beans.CrossValidationFoldMaker

Get the currently set seed

getSeed() - Method in class weka.gui.beans.TrainTestSplitMaker

Get the value of the random seed

getSegment() - Method in class weka.core.pmml.jaxbbindings.Segmentation

Gets the value of the segment property.

getSegmentId() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the segmentId property.

getSelectedAttributes() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

getSelectedAttributes() - Method in class weka.gui.AttributeSelectionPanel

Gets an array containing the indices of all selected attributes.

getSelectedBeans() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getSelectedBeans(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getSelectedBuffer() - Method in class weka.gui.ResultHistoryPanel

Gets the buffer associated with the currently selected item in the list.

getSelectedEvalMetrics() - Method in class weka.gui.EvaluationMetricSelectionDialog

Get the list of selected evaluation metrics

getSelectedName() - Method in class weka.gui.ResultHistoryPanel

Get the name of the currently selected item in the list

getSelectedObject() - Method in class weka.gui.ResultHistoryPanel

Gets the object associated with the currently selected item in the list.

getSelectedRange() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Get the value of m_SelectedRange.

getSelectedTag() - Method in class weka.core.SelectedTag

Gets the selected Tag.

getSelection() - Method in class weka.core.Range

Gets an array containing all the selected values, in the order that they were selected (or ascending order if range inversion is on).

getSelectionModel() - Method in class weka.gui.AttributeListPanel

Gets the selection model used by the table.

getSelectionModel() - Method in class weka.gui.AttributeSelectionPanel

Gets the selection model used by the table.

getSelectionModel() - Method in class weka.gui.ResultHistoryPanel

Gets the selection model used by the results list.

getSeperator() - Method in class weka.gui.HierarchyPropertyParser

Get the seperator between levels.

getSeqId() - Method in class weka.core.pmml.jaxbbindings.SequenceReference

Gets the value of the seqId property.

getSequenceModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the sequenceModel property.

getSequenceReference() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence

Gets the value of the sequenceReference property.

getSequenceReference() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence

Gets the value of the sequenceReference property.

getSerializedClassifierFile() - Method in class weka.filters.supervised.attribute.AddClassification

Gets the file pointing to a serialized, trained classifier.

getSerializedClustererFile() - Method in class weka.filters.unsupervised.attribute.AddCluster

Gets the file pointing to a serialized, built clusterer.

getSetId() - Method in class weka.core.pmml.jaxbbindings.SetReference

Gets the value of the setId property.

getSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent

Get the set number (ie which fold this is)

getSetNumber() - Method in class weka.gui.beans.BatchClustererEvent

Get the set number (ie which fold this is)

getSetNumber() - Method in class weka.gui.beans.TestSetEvent

Get the test set number (eg.

getSetNumber() - Method in class weka.gui.beans.TrainingSetEvent

Get the set number (eg.

getSetReference() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the setReference property.

getShape() - Method in class weka.gui.treevisualizer.Node

Get the value of shape.

getShapeSize() - Method in class weka.gui.visualize.PlotData2D

Get the shape sizes for the plot data

getShapeType() - Method in class weka.gui.visualize.PlotData2D

Get the shape types for the plot data

getShowAttBars() - Method in class weka.gui.visualize.VisualizePanel

Gets whether or not attribute bars are being displayed.

getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffPanel

Returns whether to display the attribute index in the header.

getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffSortedTableModel

Returns whether to display the attribute index in the header.

getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffTableModel

Returns whether to display the attribute index in the header.

getShowAverage() - Method in class weka.experiment.ResultMatrix

returns whether average per column is displayed or not.

getShowAverage() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns whether the Average is shown by default.

getShowClassPanel() - Method in class weka.gui.visualize.VisualizePanel

Gets whether or not the class panel is being displayed.

getShowStdDev() - Method in class weka.experiment.ResultMatrix

returns whether std deviations are displayed or not.

getShowStdDevs() - Method in class weka.experiment.PairedTTester

Returns true if standard deviations have been requested.

getShowStdDevs() - Method in interface weka.experiment.Tester

Returns true if standard deviations have been requested.

getShowStdDevs() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns whether StdDevs are shown by default.

getShowZeroInstancesAsUnknown() - Method in class weka.gui.InstancesSummaryPanel

Get whether to show zero instances as unknown (i.e.

getShrinkage() - Method in class weka.classifiers.meta.AdditiveRegression

Get the shrinkage rate.

getShrinkage() - Method in class weka.classifiers.meta.LogitBoost

Get the value of Shrinkage.

getSigma() - Method in class weka.attributeSelection.ReliefFAttributeEval

Get the value of sigma.

getSigma() - Method in class weka.classifiers.BVDecompose

Get the calculated sigma squared

getSigma() - Method in class weka.classifiers.functions.supportVector.Puk

Gets the sigma value.

getSignificance(int, int) - Method in class weka.experiment.ResultMatrix

returns the significance at the given position, if the position is valid, otherwise SIGNIFICANCE_ATIE.

getSignificance() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default significance.

getSignificanceCount(int, int) - Method in class weka.experiment.ResultMatrix

counts the occurrences of the given significance type in the given column.

getSignificanceLevel() - Method in class weka.associations.Apriori

Get the value of significanceLevel.

getSignificanceLevel() - Method in class weka.experiment.PairedTTester

Get the value of SignificanceLevel.

getSignificanceLevel() - Method in interface weka.experiment.Tester

Get the value of SignificanceLevel.

getSignificanceLevel() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Gets the significance level.

getSignificanceWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the significance.

getSilent() - Method in class weka.core.Check

Get whether silent mode is turned on

getSilent() - Method in class weka.core.Javadoc

whether output in the console is suppressed

getSilent() - Method in class weka.estimators.CheckEstimator

Get whether silent mode is turned on

getSimilarityScale() - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Gets the value of the similarityScale property.

getSimilarityType() - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity

Gets the value of the similarityType property.

getSimpleMatching() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the simpleMatching property.

getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the simplePredicate property.

getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the simplePredicate property.

getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the simplePredicate property.

getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the simplePredicate property.

getSimplePredicateOrCompoundPredicateOrSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate

Gets the value of the simplePredicateOrCompoundPredicateOrSimpleSetPredicate property.

getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the simpleSetPredicate property.

getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the simpleSetPredicate property.

getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the simpleSetPredicate property.

getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the simpleSetPredicate property.

getSimpleStats(int) - Method in class weka.classifiers.rules.RuleStats

Get the simple stats of one rule, including 6 parameters: 0: coverage; 1:uncoverage; 2: true positive; 3: true negatives; 4: false positives; 5: false negatives

getSIndex() - Method in class weka.gui.visualize.VisualizePanel

Get the index of the shape selected for creating splits.

getSingleIndex() - Method in class weka.core.SingleIndex

Gets the string representing the selected range of values.

getSingleLineCommentStart() - Method in class weka.gui.scripting.SyntaxDocument

Retrusn the single line comment start string.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.LED24

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the single mode flag.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.regression.Expression

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleModeFlag() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Gets the single mode flag.

getSingleModeFlag() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Gets the single mode flag.

getSingleModeFlag() - Method in class weka.datagenerators.DataGenerator

Return if single mode is set for the given data generator mode depends on option setting and or generator type.

getSingleton() - Static method in class weka.core.logging.Logger

Returns the singleton instance of the logger.

getSingleton() - Static method in class weka.gui.beans.KnowledgeFlowApp

Return the singleton instance of the KnowledgeFlow

getSingleton() - Static method in class weka.gui.GUIChooser

Get the singleton instance of the GUIChooser

getSingleton() - Static method in class weka.gui.Main

Return the singleton instance of the Main GUI.

getSingularValues() - Method in class weka.core.matrix.SingularValueDecomposition

Return the one-dimensional array of singular values

getSize() - Method in class weka.core.Debug.Log

returns the size of the files

getSize() - Method in class weka.core.pmml.jaxbbindings.Cluster

Gets the value of the size property.

getSize() - Method in class weka.core.pmml.jaxbbindings.Partition

Gets the value of the size property.

getSize() - Method in class weka.gui.beans.EnvironmentField.WideComboBox

getSkipIdentical() - Method in class weka.core.neighboursearch.LinearNNSearch

Gets whether if identical instances are skipped from the neighbourhood.

getSlope() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns the slope of the function.

getSlope() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression

Returns the slope of the function.

getSmoothedValue() - Method in class weka.core.pmml.jaxbbindings.Level

Gets the value of the smoothedValue property.

getSmoothedValue() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Gets the value of the smoothedValue property.

getSmoothing() - Method in class weka.classifiers.trees.m5.Rule

Get whether or not smoothing has been turned on

getSort() - Method in class weka.filters.unsupervised.attribute.AddValues

Gets whether the labels are sorted or not.

getSortColumn() - Method in class weka.experiment.PairedTTester

Returns the column to sort on, -1 means the default sorting.

getSortColumn() - Method in interface weka.experiment.Tester

Returns the column to sort on, -1 means the default sorting.

getSortColumnName() - Method in class weka.experiment.PairedTTester

Returns the name of the column to sort on.

getSortColumnName() - Method in interface weka.experiment.Tester

Returns the name of the column to sort on.

getSortDetails() - Method in class weka.gui.beans.Sorter

Get the sort rules to use

getSorting() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default sorting (empty string means none).

getSortType() - Method in class weka.filters.unsupervised.attribute.SortLabels

Gets the sort type to be used.

getSource() - Method in class weka.gui.beans.BeanConnection

returns the source BeanInstance for this connection

getSource() - Method in class weka.gui.treevisualizer.Edge

Get the value of source.

getSourceCode() - Method in class weka.classifiers.CheckSource

Gets the class to test.

getSourceCode() - Method in class weka.filters.CheckSource

Gets the class to test.

getSparseData() - Method in class weka.core.converters.DatabaseLoader

Gets whether data is to be returned as a set of sparse instances

getSparseData() - Method in class weka.experiment.InstanceQuery

Gets whether data is to be returned as a set of sparse instances

getSparseData() - Method in interface weka.experiment.InstanceQueryAdapter

Gets whether data is to be returned as a set of sparse instances

getSplitByDataSet() - Method in class weka.experiment.RemoteExperiment

Returns true if sub experiments are to be created on the basis of data set..

getSplitCharacteristic() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the splitCharacteristic property.

getSplitCharacteristic() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the splitCharacteristic property.

getSplitConfidence() - Method in class weka.classifiers.trees.HoeffdingTree

Get the allowable error in a split decision.

getSplitCriterion() - Method in class weka.classifiers.trees.HoeffdingTree

Get the split criterion to use (either Gini or info gain).

getSplitDim() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode

Gets the splitting dimension.

getSplitEvaluator() - Method in class weka.experiment.CrossValidationResultProducer

Get the SplitEvaluator.

getSplitEvaluator() - Method in class weka.experiment.ExplicitTestsetResultProducer

Get the SplitEvaluator.

getSplitEvaluator() - Method in class weka.experiment.RandomSplitResultProducer

Get the SplitEvaluator.

getSplitOnResiduals() - Method in class weka.classifiers.trees.LMT

Get the value of splitOnResiduals.

getSplitPoint() - Method in class weka.associations.NumericItem

Gets the numeric test.

getSplitPoint() - Method in class weka.classifiers.rules.JRip.NumericAntd

Get split point of this numeric antecedent

getSplitPoint() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Get the split point used for numeric selection

getSplitValue() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode

Gets the splitting value.

getSpreadInitialCount() - Method in class weka.classifiers.trees.REPTree

Get the value of SpreadInitialCount.

getSqlWhere() - Method in class weka.core.pmml.jaxbbindings.Aggregate

Gets the value of the sqlWhere property.

getSquaredError() - Method in class weka.clusterers.SimpleKMeans

Gets the squared error for all clusters.

getSquaredEuclidean() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the squaredEuclidean property.

getSSB() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Gets the value of the ssb property.

getSSE() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Gets the value of the sse property.

getStamp() - Method in class weka.core.Debug.Timestamp

returns the associated date/time

getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcesses

Gives standard deviation of the prediction at the given instance.

getStandardDeviation() - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Gets the value of the standardDeviation property.

getStandardDeviation() - Method in class weka.core.pmml.jaxbbindings.Time

Gets the value of the standardDeviation property.

getStandardError() - Method in class weka.core.pmml.jaxbbindings.TimeValue

Gets the value of the standardError property.

getStart() - Method in class weka.core.Debug.Clock

returns the start time

getStartMessage() - Method in class weka.gui.beans.Loader

Gets a string that describes the start action.

getStartMessage() - Method in class weka.gui.beans.MetaBean

getStartMessage() - Method in interface weka.gui.beans.Startable

Gets a string that describes the start action.

getStartPoints(Integer...) - Static method in class weka.gui.beans.BeanInstance

Returns a list of start points (if any) in the indexed flow

getStartSequentially() - Method in class weka.gui.beans.FlowRunner

Gets whether Startable beans will be launched sequentially or all in parallel.

getStartSet() - Method in class weka.attributeSelection.BestFirst

Returns a list of attributes (and or attribute ranges) as a String

getStartSet() - Method in class weka.attributeSelection.GreedyStepwise

Returns a list of attributes (and or attribute ranges) as a String

getStartSet() - Method in class weka.attributeSelection.Ranker

Returns a list of attributes (and or attribute ranges) as a String

getStartSet() - Method in interface weka.attributeSelection.StartSetHandler

Returns a list of attributes (and or attribute ranges) as a String

getStartTime() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the startTime property.

getStartTimeVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the startTimeVariable property.

getStaticIcon() - Method in class weka.gui.beans.BeanVisual

Returns the static icon

getStatistic(String) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Get the value of the named statistic

getStatistic(String, int) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric

Get the value of the named statistic for the given class index.

getStatisticNames() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Get a list of the names of the statistics that this metrics computes.

getStats() - Method in class weka.core.neighboursearch.PerformanceStats

Returns a string representation of the statistics.

getStats() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns a string representation of the statistics.

getStatus() - Method in class weka.gui.beans.IncrementalClassifierEvent

Get the status

getStatus() - Method in class weka.gui.beans.InstanceEvent

Get the status

getStatusFrequency() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Get how often progress is reported to the status bar.

getStatusMessage() - Method in class weka.experiment.TaskStatusInfo

Get the status message.

getStatusTable() - Method in class weka.gui.beans.LogPanel

The JTable used for the status messages (in case clients want to attach listeners etc.)

getStatusVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the statusVariable property.

getStdDev() - Method in class weka.estimators.KernelEstimator

Return the standard deviation of this kernel estimator.

getStdDev() - Method in class weka.estimators.NormalEstimator

Return the value of the standard deviation of this normal estimator.

getStdDev(int, int) - Method in class weka.experiment.ResultMatrix

returns the std deviation at the given position, if the position is valid, otherwise 0.

getStdDevCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the standard deviation of coords per point.

getStdDevIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the standard deviation of internal nodes visited.

getStdDevLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the standard deviation of leaves visited.

getStdDevPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the standard deviation of points visited.

getStdDevPrec() - Method in class weka.experiment.ResultMatrix

returns the current standard deviation precision.

getStdDevPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the default precision for the stddevs.

getStddevValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

getStdDevWidth() - Method in class weka.experiment.ResultMatrix

returns the current width for the std dev.

getStdError() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the stdError property.

getStemmer() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the current stemming algorithm, null if none is used.

getStemmer() - Method in class weka.classifiers.functions.SGDText

Returns the current stemming algorithm, null if none is used.

getStemmer() - Method in class weka.core.stemmers.SnowballStemmer

returns the name of the current stemmer, null if none is set.

getStemmer() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the current stemming algorithm, null if none is used.

getStepsize() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the stepsize property.

getStepSize() - Method in class weka.experiment.LearningRateResultProducer

Get the value of StepSize.

getStop() - Method in class weka.core.Debug.Clock

returns the stop time or, if still running, the current time

getStopwords() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

returns the file used for obtaining the stopwords, if the file represents a directory then the default ones are used.

getStopwords() - Method in class weka.classifiers.functions.SGDText

returns the file used for obtaining the stopwords, if the file represents a directory then the default ones are used.

getStopwords() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

returns the file used for obtaining the stopwords, if the file represents a directory then the default ones are used.

getString() - Method in class weka.core.Trie.TrieNode

returns the full string up to the root

getStringAttributes() - Method in class weka.core.converters.CSVLoader

Returns the current attribute range to be forced to type string.

getStringSelection() - Method in class weka.gui.arffviewer.ArffTable

returns the selected content in a StringSelection that can be copied to the clipboard and used in Excel, if nothing is selected the whole table is copied to the clipboard

getStroke() - Method in class weka.gui.visualize.PostscriptGraphics

getStructure() - Method in class weka.core.converters.AbstractLoader

getStructure() - Method in class weka.core.converters.ArffLoader.ArffReader

Returns the header format

getStructure() - Method in class weka.core.converters.ArffLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.C45Loader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.ConverterUtils.DataSource

returns the structure of the data.

getStructure(int) - Method in class weka.core.converters.ConverterUtils.DataSource

returns the structure of the data, with the defined class index.

getStructure() - Method in class weka.core.converters.CSVLoader

getStructure() - Method in class weka.core.converters.DatabaseLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.JSONLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.LibSVMLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in interface weka.core.converters.Loader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.MatlabLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.SerializedInstancesLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.SVMLightLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.TextDirectoryLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.XRFFLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure(String) - Method in class weka.gui.beans.Associator

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.ClassAssigner

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.ClassValuePicker

getStructure(String) - Method in class weka.gui.beans.CrossValidationFoldMaker

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.FlowByExpression

Get the structure of the output encapsulated in the named event.

getStructure() - Method in class weka.gui.beans.IncrementalClassifierEvent

Get the instances structure (may be null if this is not a NEW_BATCH event)

getStructure() - Method in class weka.gui.beans.InstanceEvent

Get the instances structure (may be null if this is not a FORMAT_AVAILABLE event)

getStructure(String) - Method in class weka.gui.beans.Join

Get the output instances structure given an input event type

getStructure(String) - Method in class weka.gui.beans.Loader

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.Sorter

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in interface weka.gui.beans.StructureProducer

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.TestSetMaker

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.TrainingSetMaker

Get the structure of the output encapsulated in the named event.

getStructure(String) - Method in class weka.gui.beans.TrainTestSplitMaker

Get the structure of the output encapsulated in the named event.

getSubFlow() - Method in class weka.gui.beans.MetaBean

getSubjectIDVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the subjectIDVariable property.

getSubmenuTitle() - Method in interface weka.gui.MainMenuExtension

Returns the name of the submenu.

getSubsequenceLength() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the length of the subsequence

getSubSpaceSize() - Method in class weka.classifiers.meta.RandomSubSpace

Gets the size of each subSpace, as a percentage of the training set size.

getSubtreeRaising() - Method in class weka.classifiers.trees.J48

Get the value of subtreeRaising.

getSuccess() - Method in class weka.core.CheckGOE

returns the success of the tests

getSuccess() - Method in class weka.core.CheckOptionHandler

returns the success of the tests

getSuitableTargets(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean

Return a list of input beans capable of receiving the supplied event

getSummary() - Method in class weka.gui.SetInstancesPanel

Gets the instances summary panel associated with this panel.

getSumOfCounts() - Method in class weka.estimators.DiscreteEstimator

Get the sum of all the counts

getSumOfSquares() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the sumOfSquares property.

getSumOfWeights() - Method in class weka.estimators.NormalEstimator

Return the sum of the weights for this normal estimator.

getSumSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the sumSquaredError property.

getSumSquaredRegression() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the sumSquaredRegression property.

getSupport() - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Gets the value of the support property.

getSupport() - Method in class weka.core.pmml.jaxbbindings.Itemset

Gets the value of the support property.

getSupport() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the support property.

getSupport() - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Gets the value of the support property.

getSupportedCursorScrollType() - Method in class weka.experiment.DatabaseUtils

Returns the type of scrolling that the cursor supports, -1 if not supported or not connected.

getSupportVector() - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Gets the value of the supportVector property.

getSupportVectorMachineModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the supportVectorMachineModel property.

getSupportVectors() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the supportVectors property.

getSuppressMappingReport() - Method in class weka.classifiers.misc.InputMappedClassifier

Get whether to suppress output the report of model to input mappings.

getSuppressOutput() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns whether to the regular output is suppressed in case the output is stored in a file.

getSvmRepresentation() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the svmRepresentation property.

getSymbols() - Method in class weka.core.mathematicalexpression.Parser

Returns the current variable - value relation in use.

getSymbols() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Returns the current variable - value relation in use.

getSystemInfo() - Method in class weka.core.SystemInfo

returns a copy of the system info.

getSystemLookAndFeel() - Static method in class weka.gui.LookAndFeel

returns the system LnF classname

getSystemWide() - Static method in class weka.core.Environment

Get the singleton system-wide (visible to every class in the running VM) set of environment variables.

getT1() - Method in class weka.clusterers.Canopy

Get the T1 distance.

getT2() - Method in class weka.clusterers.Canopy

Get the T2 distance to use.

getTabbedPane() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

returns the tabbedpane instance

getTabbedPane() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getTabbedPane() - Method in class weka.gui.explorer.Explorer

returns the tabbed pane of the Explorer

getTable() - Method in class weka.gui.arffviewer.ArffPanel

returns the table component

getTable() - Method in class weka.gui.beans.InteractiveTablePanel

Get the JTable component

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class weka.gui.arffviewer.ArffTableCellRenderer

Returns the default table cell renderer.

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class weka.gui.sql.ResultSetTableCellRenderer

Returns the default table cell renderer.

getTableLocator() - Method in class weka.core.pmml.jaxbbindings.ChildParent

Gets the value of the tableLocator property.

getTableLocator() - Method in class weka.core.pmml.jaxbbindings.MapValues

Gets the value of the tableLocator property.

getTableLocator() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the tableLocator property.

getTableModel() - Method in class weka.gui.AttributeSelectionPanel

Get the table model in use (or null if no instances have been set yet).

getTableName() - Method in class weka.core.converters.DatabaseSaver

Gets the table's name.

getTabs() - Static method in class weka.gui.explorer.ExplorerDefaults

returns an array with the classnames of all the additional panels to display as tabs in the Explorer.

getTabTitle(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getTabTitle() - Method in class weka.gui.explorer.AssociationsPanel

Returns the title for the tab in the Explorer

getTabTitle() - Method in class weka.gui.explorer.AttributeSelectionPanel

Returns the title for the tab in the Explorer

getTabTitle() - Method in class weka.gui.explorer.ClassifierPanel

Returns the title for the tab in the Explorer.

getTabTitle() - Method in class weka.gui.explorer.ClustererPanel

Returns the title for the tab in the Explorer

getTabTitle() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel

Returns the title for the tab in the Explorer

getTabTitle() - Method in class weka.gui.explorer.PreprocessPanel

Returns the title for the tab in the Explorer

getTabTitle() - Method in class weka.gui.explorer.VisualizePanel

Returns the title for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.AssociationsPanel

Returns the tooltip for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.AttributeSelectionPanel

Returns the tooltip for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.ClassifierPanel

Returns the tooltip for the tab in the Explorer.

getTabTitleToolTip() - Method in class weka.gui.explorer.ClustererPanel

Returns the tooltip for the tab in the Explorer

getTabTitleToolTip() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel

Returns the tooltip for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.PreprocessPanel

Returns the tooltip for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.VisualizePanel

Returns the tooltip for the tab in the Explorer

getTabuList() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

getTabuList() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

getTags() - Method in class weka.core.SelectedTag

Gets the set of all valid Tags.

getTags() - Method in class weka.gui.beans.EnvironmentField

getTags() - Method in class weka.gui.CostMatrixEditor

Some objects can return tags, but a cost matrix cannot.

getTags() - Method in class weka.gui.GenericArrayEditor

Returns null as we don't support getting values as tags.

getTags() - Method in class weka.gui.GenericObjectEditor

Returns null as we don't support getting values as tags.

getTags() - Method in class weka.gui.SelectedTagEditor

Gets the list of tags that can be selected from.

getTags() - Method in class weka.gui.SimpleDateFormatEditor

Some objects can return tags, but a date format cannot.

getTanimoto() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Gets the value of the tanimoto property.

getTarget() - Method in class weka.core.pmml.jaxbbindings.Anova

Gets the value of the target property.

getTarget() - Method in class weka.core.pmml.jaxbbindings.Targets

Gets the value of the target property.

getTarget() - Method in class weka.gui.beans.BeanConnection

Returns the target BeanInstance for this connection

getTarget() - Method in class weka.gui.treevisualizer.Edge

Get the value of target.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats

Gets the value of the targetCategory property.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PCell

Gets the value of the targetCategory property.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the targetCategory property.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PPCell

Gets the value of the targetCategory property.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Gets the value of the targetCategory property.

getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the targetCategory property.

getTargetField() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the targetField property.

getTargetField() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Gets the value of the targetField property.

getTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the targetFieldDisplayValue property.

getTargetFieldName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the targetFieldName property.

getTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.LiftData

Gets the value of the targetFieldValue property.

getTargetMetaData() - Method in class weka.core.pmml.MiningSchema

Get the Target meta data.

getTargetReferenceCategory() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the targetReferenceCategory property.

getTargets() - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Gets the value of the targets property.

getTargets() - Method in class weka.core.pmml.jaxbbindings.Regression

Gets the value of the targets property.

getTargetValue() - Method in class weka.core.pmml.jaxbbindings.Target

Gets the value of the targetValue property.

getTargetValueCount() - Method in class weka.core.pmml.jaxbbindings.TargetValueCounts

Gets the value of the targetValueCount property.

getTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.BayesOutput

Gets the value of the targetValueCounts property.

getTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.PairCounts

Gets the value of the targetValueCounts property.

getTargetVariableName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the targetVariableName property.

getTaskResult() - Method in class weka.experiment.TaskStatusInfo

Get the returnable result of this task.

getTaskStatus() - Method in class weka.experiment.RemoteExperimentSubTask

getTaskStatus() - Method in interface weka.experiment.Task

Clients should be able to call this method at any time to obtain information on a current task.

getTaskStatus() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Return status information for this sub task

getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.DataDictionary

Gets the value of the taxonomy property.

getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the taxonomy property.

getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.TextDictionary

Gets the value of the taxonomy property.

getTCol() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the tCol property.

getTechnicalInformation() - Method in class weka.associations.Apriori

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.associations.FPGrowth

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.attributeSelection.CfsSubsetEval

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayes

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.ADNode

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.BIFReader

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.K2

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.TAN

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.K2

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.TAN

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.BVDecompose

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.BVDecomposeSegCVSub

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcesses

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.Logistic

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.SimpleLogistic

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.SMO

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.SMOreg

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.Puk

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.RegSMO

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.VotedPerceptron

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.lazy.IBk

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.lazy.KStar

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.lazy.LWL

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.AdaBoostM1

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.AdditiveRegression

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.Bagging

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.ClassificationViaRegression

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.CVParameterSelection

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.LogitBoost

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.RandomSubSpace

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.Stacking

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.Vote

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.rules.DecisionTable

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.rules.JRip

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.rules.M5Rules

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.rules.OneR

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.rules.PART

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.HoeffdingTree

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.J48

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.LMT

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.m5.M5Base

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.RandomForest

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.clusterers.Canopy

getTechnicalInformation() - Method in class weka.clusterers.Cobweb

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.clusterers.FarthestFirst

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.clusterers.SimpleKMeans

getTechnicalInformation() - Method in class weka.core.ChebyshevDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.ConjugateGradientOptimization

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.EuclideanDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.ManhattanDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.MinkowskiDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.BallTree

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.CoverTree

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.KDTree

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.Optimization

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.stemmers.LovinsStemmer

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in interface weka.core.TechnicalInformationHandler

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.datagenerators.classifiers.classification.LED24

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.experiment.PairedCorrectedTTester

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.supervised.attribute.Discretize

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.supervised.attribute.NominalToBinary

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTempDir() - Static method in class weka.core.Debug

returns the system temp directory

getTempDirectory() - Method in class weka.gui.beans.Sorter

Get the directory to use for temporary files during incremental operation

getTester() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the display name of the preferred Tester algorithm.

getTestEvaluator() - Method in class weka.attributeSelection.CheckAttributeSelection

Gets whether the evaluator is being tested or the search method.

getTestOrTrain() - Method in class weka.gui.beans.BatchClustererEvent

Get whether the set of instances is a test or a training set

getTestPredictions(Classifier, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils

Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.

getTestSet() - Method in class weka.gui.beans.BatchClassifierEvent

Get the test set

getTestSet() - Method in class weka.gui.beans.BatchClustererEvent

Get the training/test set

getTestSet() - Method in class weka.gui.beans.TestSetEvent

Get the test set instances

getTestsetDir() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the currently set directory for the test sets.

getTestsetPrefix() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the currently set prefix.

getTestsetSuffix() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the currently set suffix.

getTestStatistic() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the testStatistic property.

getText() - Method in class weka.gui.beans.BeanVisual

Get the visual's label

getText() - Method in class weka.gui.beans.EnvironmentField

Return the text from the combo box.

getText() - Method in class weka.gui.beans.TextEvent

Describe getText method here.

getTextDocument() - Method in class weka.core.pmml.jaxbbindings.TextCorpus

Gets the value of the textDocument property.

getTextModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the textModel property.

getTextTitle() - Method in class weka.gui.beans.TextEvent

Describe getTextTitle method here.

getTFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.

getThreshold() - Method in class weka.attributeSelection.GreedyStepwise

Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.

getThreshold() - Method in interface weka.attributeSelection.RankedOutputSearch

Gets the threshold by which attributes can be discarded.

getThreshold() - Method in class weka.attributeSelection.Ranker

Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.

getThreshold() - Method in class weka.attributeSelection.WrapperSubsetEval

Get the value of the threshold

getThreshold() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the value of the threshold property.

getThreshold() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the threshold property.

getThreshold() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the threshold property.

getThreshold() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the threshold property.

getThreshold() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Gets the value of the threshold property.

getThreshold() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the threshold property.

getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Gets the threshold for the max error when predicting a numeric class.

getThresholdInstance(Instances, double) - Static method in class weka.classifiers.evaluation.ThresholdCurve

Gets the index of the instance with the closest threshold value to the desired target

getTime() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence

Gets the value of the time property.

getTime() - Method in class weka.core.pmml.jaxbbindings.BaselineCell

Gets the value of the time property.

getTime() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence

Gets the value of the time property.

getTime() - Method in class weka.core.pmml.jaxbbindings.Sequence

Gets the value of the time property.

getTime() - Method in class weka.core.pmml.jaxbbindings.TimeValue

Gets the value of the time property.

getTimeAnchor() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the timeAnchor property.

getTimeCycle() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the timeCycle property.

getTimeException() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the timeException property.

getTimeSeriesModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the timeSeriesModel property.

getTimestamp() - Method in class weka.core.pmml.jaxbbindings.Header

Gets the value of the timestamp property.

getTimestamp() - Method in class weka.core.pmml.jaxbbindings.TimeValue

Gets the value of the timestamp property.

getTimestamp() - Static method in class weka.experiment.CrossValidationResultProducer

Gets a Double representing the current date and time.

getTimestamp() - Static method in class weka.experiment.ExplicitTestsetResultProducer

Gets a Double representing the current date and time.

getTimestamp() - Static method in class weka.experiment.RandomSplitResultProducer

Gets a Double representing the current date and time.

getTimeValue() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the timeValue property.

getTimeValue() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the timeValue property.

getTitle() - Method in class weka.gui.arffviewer.ArffPanel

returns the title for the Tab, i.e.

getTitle() - Method in class weka.gui.scripting.FileScriptingPanel

Returns the current title for the frame/dialog.

getTitle() - Method in class weka.gui.scripting.ScriptingPanel

Returns the current title for the frame/dialog.

getTitle() - Method in class weka.gui.SimpleCLIPanel

Returns the current title for the frame/dialog.

getToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils

Gets token.

getToken(StreamTokenizer) - Static method in class weka.core.converters.StreamTokenizerUtils

Gets token.

getTokenizer() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the current tokenizer algorithm.

getTokenizer() - Method in class weka.classifiers.functions.SGDText

Returns the current tokenizer algorithm.

getTokenizer() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the current tokenizer algorithm.

getTolerance() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

returns the current tolerance

getToleranceParameter() - Method in class weka.classifiers.functions.SMO

Get the value of tolerance parameter.

getToolTipLocation(MouseEvent) - Method in class weka.gui.ETable

Places tool tips over the cell they correspond to.

getToolTipText() - Method in class weka.experiment.PairedCorrectedTTester

returns a string that is displayed as tooltip on the "perform test" button in the experimenter

getToolTipText() - Method in class weka.experiment.PairedTTester

returns a string that is displayed as tooltip on the "perform test" button in the experimenter

getToolTipText() - Method in interface weka.experiment.Tester

returns a string that is displayed as tooltip on the "perform test" button in the experimenter

getToolTipText(MouseEvent) - Method in class weka.gui.AttributeVisualizationPanel

Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.

getToolTipText() - Method in class weka.gui.GenericObjectEditor.GOETreeNode

Get the tool tip for this node

getToolTipText(PrintableComponent) - Static method in class weka.gui.visualize.PrintableComponent

Returns a tooltip only if the user wants it.

getTop() - Method in class weka.gui.treevisualizer.Node

Get the value of top.

getTotalCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the total sum of coords per point.

getTotalCount(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the total number of nodes there are.

getTotalFreq() - Method in class weka.core.pmml.jaxbbindings.Counts

Gets the value of the totalFreq property.

getTotalGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the total number of groups of siblings there are.

getTotalHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node

Recursively finds the total number of levels there are.

getTotalIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the total number of internal nodes visited.

getTotalLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats

Returns the total number of leaves visited.

getTotalPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats

Returns the total number of points visited.

getTotalSquaresSum() - Method in class weka.core.pmml.jaxbbindings.ContStats

Gets the value of the totalSquaresSum property.

getTotalSupport() - Method in class weka.associations.AssociationRule

Get the total support for this rule (premise + consequence).

getTotalSupport() - Method in class weka.associations.DefaultAssociationRule

getTotalTransactions() - Method in class weka.associations.AssociationRule

Get the total number of transactions in the data.

getTotalTransactions() - Method in class weka.associations.DefaultAssociationRule

getTotalValuesSum() - Method in class weka.core.pmml.jaxbbindings.ContStats

Gets the value of the totalValuesSum property.

getToYear() - Static method in class weka.core.Copyright

returns the end year of the copyright (i.e., current year)

getTrainingSet() - Method in class weka.gui.beans.TrainingSetEvent

Get the training instances

getTrainingTime() - Method in class weka.classifiers.functions.MultilayerPerceptron

getTrainIterations() - Method in class weka.classifiers.BVDecompose

Gets the maximum number of boost iterations

getTrainPercent() - Method in class weka.experiment.RandomSplitResultProducer

Get the value of TrainPercent.

getTrainPercent() - Method in class weka.gui.beans.TrainTestSplitMaker

Get the percentage of the data that will be in the training portion of the split

getTrainPercentage() - Static method in class weka.gui.experiment.ExperimenterDefaults

returns the training percentage in case of splits.

getTrainPoolSize() - Method in class weka.classifiers.BVDecompose

Get the number of instances in the training pool.

getTrainSet() - Method in class weka.gui.beans.BatchClassifierEvent

Get the train set

getTrainSize() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the training size

getTrainTestPredictions(Classifier, Instances, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils

Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.

getTransactionsMustContain() - Method in class weka.associations.FPGrowth

Gets the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.

getTransform() - Method in class weka.gui.visualize.PostscriptGraphics

getTransformAllValues() - Method in class weka.filters.supervised.attribute.NominalToBinary

Gets if all nominal values are turned into new attributes, not only if there are more than 2.

getTransformAllValues() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Gets if all nominal values are turned into new attributes, not only if there are more than 2.

getTransformation() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the transformation property.

getTransformationDictionary() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the transformationDictionary property.

getTransformationDictionary() - Method in class weka.core.pmml.MiningSchema

Get the transformation dictionary .

getTransformBackToOriginal() - Method in class weka.attributeSelection.PrincipalComponents

Gets whether the data is to be transformed back to the original space.

getTranslation() - Method in class weka.filters.unsupervised.attribute.Normalize

Get the translation.

getTreatMissingValuesAsZero() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Get whether missing values are to be treated in the same way as zeros

getTreatZeroAsMissing() - Method in class weka.associations.Apriori

Gets whether zeros (i.e.

getTreeModel() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the treeModel property.

getTreeRoot() - Method in class weka.clusterers.Cobweb

Get the root of the tree.

getTrend() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Gets the value of the trend property.

getTrendExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Gets the value of the trendExpoSmooth property.

getTrialsValue() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the trialsValue property.

getTrialsVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the trialsVariable property.

getTrim() - Method in class weka.classifiers.misc.InputMappedClassifier

Get whether to trim white space from each end of names before matching.

getTRow() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the tRow property.

getTrue() - Method in class weka.core.pmml.jaxbbindings.Attribute

Gets the value of the true property.

getTrue() - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Gets the value of the true property.

getTrue() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the true property.

getTrue() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the true property.

getTrueNegative() - Method in class weka.classifiers.evaluation.TwoClassStats

Gets the number of negative instances predicted as negative

getTruePositive() - Method in class weka.classifiers.evaluation.TwoClassStats

Gets the number of positive instances predicted as positive

getTruePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats

Calculate the true positive rate.

getTrueStepName() - Method in class weka.gui.beans.FlowByExpression

Get the name of the connected step to send "true" instances to

getTruncate() - Method in class weka.core.converters.DatabaseSaver

Get whether to truncate (i.e.

getTStart() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

getTStart() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

getTValue() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the tValue property.

getTwoClassStats(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix

Gets the performance with respect to one of the classes as a TwoClassStats object.

getType() - Method in class weka.classifiers.functions.neural.NeuralConnection

getType() - Method in class weka.core.AttributeLocator

returns the type of attribute that is located

getType() - Method in class weka.core.pmml.Array

Get the type of this array.

getType() - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.ArrayType

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Gets the value of the type property.

getType() - Method in class weka.core.pmml.jaxbbindings.TimeException

Gets the value of the type property.

getType(RevisionHandler) - Static method in class weka.core.RevisionUtils

Determines the type of a (sanitized) revision string returned by the RevisionHandler.

getType(String) - Static method in class weka.core.RevisionUtils

Determines the type of a (sanitized) revision string.

getType() - Method in class weka.core.TechnicalInformation

returns the type of this technical information

getType() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the type of the new attribute

getType(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the TYPE of the attribute at the given position

getType(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns the TYPE of the attribute at the given position

getType(int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the TYPE of the attribute at the given position

getType(int, int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the TYPE of the attribute at the given position

getType() - Method in class weka.gui.scripting.event.ScriptExecutionEvent

Returns the type of event.

getType() - Method in class weka.gui.sql.event.ConnectionEvent

returns the type of this event, CONNECT or DISCONNECT

getU() - Method in class weka.core.Matrix

Deprecated. Returns the U part of the matrix.

getU() - Method in class weka.core.matrix.LUDecomposition

Return upper triangular factor

getU() - Method in class weka.core.matrix.SingularValueDecomposition

Return the left singular vectors

getUID(String) - Static method in class weka.core.SerializationHelper

reads or creates the serialVersionUID for the given class.

getUID(Class<?>) - Static method in class weka.core.SerializationHelper

reads or creates the serialVersionUID for the given class.

getUnderlyingPackageManager() - Static method in class weka.core.WekaPackageManager

Get the underlying package manager implementation

getUndoBuffer() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getUndoBuffer(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

getUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate

Gets the value of the uniformDistribution property.

getUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline

Gets the value of the uniformDistribution property.

getUnit() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Gets the value of the unit property.

getUnivariateStats() - Method in class weka.core.pmml.jaxbbindings.ModelStats

Gets the value of the univariateStats property.

getUnpruned() - Method in class weka.classifiers.rules.PART

Get the value of unpruned.

getUnpruned() - Method in class weka.classifiers.trees.J48

Get the value of unpruned.

getUnpruned() - Method in class weka.classifiers.trees.m5.M5Base

Get whether unpruned tree/rules are being generated

getUnpruned() - Method in class weka.classifiers.trees.m5.Rule

Get whether unpruned tree/rules are being generated

getUnsortedEigenVectors() - Method in class weka.attributeSelection.PrincipalComponents

Return the unsorted eigenvectors

getUpdateCount() - Method in class weka.core.converters.DatabaseConnection

Dewtermines if the current query retrieves a result set or updates a table

getUpdateIncrementalClassifier() - Method in class weka.gui.beans.Classifier

Get whether an incremental classifier will be updated on the incoming instance stream.

getUpdateWeightsOnly() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Gets whether only weights should be udpated.*

getUpper() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution

Gets the value of the upper property.

getUpper() - Method in class weka.gui.experiment.RunNumberPanel

Gets the current upper run number.

getUpperBoundMinSupport() - Method in class weka.associations.Apriori

Get the value of upperBoundMinSupport.

getUpperBoundMinSupport() - Method in class weka.associations.FPGrowth

Get the value of upperBoundMinSupport.

getUpperCase() - Method in class weka.core.converters.DatabaseConnection

Check if the property checkUpperCaseNames in the DatabaseUtils file is set to true or false.

getUpperNumericBound() - Method in class weka.core.Attribute

Returns the upper bound of a numeric attribute.

getUpperSize() - Method in class weka.experiment.LearningRateResultProducer

Get the value of UpperSize.

getUrl() - Method in interface weka.core.converters.DatabaseConverter

getUrl() - Method in class weka.core.converters.DatabaseLoader

Gets the URL

getUrl() - Method in class weka.core.converters.DatabaseSaver

Gets the database URL.

getURL() - Static method in class weka.core.Copyright

returns the URL of the owner

getURL() - Method in class weka.gui.DatabaseConnectionDialog

Returns URL from dialog

getURL(String, String) - Static method in class weka.gui.Loader

returns a URL for the given filename, can be NULL if it fails

getURL(String) - Method in class weka.gui.Loader

returns a URL for the given filename, can be NULL if it fails

getURL() - Method in class weka.gui.sql.ConnectionPanel

returns the current URL.

getURL() - Method in class weka.gui.sql.event.ResultChangedEvent

returns the database URL that produced the table model

getURL() - Method in class weka.gui.sql.ResultSetTable

returns the database URL that produced the table model

getURL() - Method in class weka.gui.sql.SqlViewer

returns the database URL from the currently active tab in the ResultPanel, otherwise an empty string.

getURL() - Method in class weka.gui.sql.SqlViewerDialog

returns the chosen URL, if any.

getURLFileLoaders() - Static method in class weka.core.converters.ConverterUtils

returns a vector with the classnames of all the URL file loaders.

getURLLoaderForExtension(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the URL loader to use for this kind of extension, returns null if none can be found.

getURLLoaderForFile(String) - Static method in class weka.core.converters.ConverterUtils

tries to determine the URL loader to use for this kind of file, returns null if none can be found.

getURLLoaderForFile(File) - Static method in class weka.core.converters.ConverterUtils

tries to determine the URL loader to use for this kind of file, returns null if none can be found.

getUsage() - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Gets the value of the usage property.

getUsageType() - Method in class weka.core.pmml.jaxbbindings.MiningField

Gets the value of the usageType property.

getUsageType() - Method in class weka.core.pmml.MiningFieldMetaInfo

Get the usage type of this field.

getUseADTree() - Method in class weka.classifiers.bayes.BayesNet

Method declaration

getUseAIC() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of useAIC.

getUseAIC() - Method in class weka.classifiers.trees.LMT

Get the value of useAIC.

getUseAIC() - Method in class weka.classifiers.trees.lmt.LogisticBase

Get the value of useAIC.

getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

get use the arc reversal operation

getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

get use the arc reversal operation

getUseBetterEncoding() - Method in class weka.filters.supervised.attribute.Discretize

Gets whether better encoding is to be used for MDL.

getUseBinNumbers() - Method in class weka.filters.supervised.attribute.Discretize

Gets whether bin numbers rather than ranges should be used for discretized attributes.

getUseBinNumbers() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets whether bin numbers rather than ranges should be used for discretized attributes.

getUseBlanks() - Method in class weka.gui.scripting.SyntaxDocument

Returns whether blanks are used instead of tabs.

getUseClassification() - Static method in class weka.gui.experiment.ExperimenterDefaults

whether classification or regression is used.

getUseConjugateGradientDescent() - Method in class weka.classifiers.functions.Logistic

Gets whether to use conjugate gradient descent rather than BFGS updates.

getUseCpuTime() - Method in class weka.core.Debug.Clock

returns whether the use of CPU is time is enabled/disabled (regardless whether the system supports it or not)

getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getUseCrossValidation() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of useCrossValidation.

getUseCustomDimensions() - Method in class weka.gui.visualize.JComponentWriter

whether custom dimensions are to used for the size of the image

getUsedAttributes() - Method in class weka.classifiers.trees.lmt.LogisticBase

Returns an array of the indices of the attributes used in the logistic model.

getUseDouble() - Method in class weka.core.converters.MatlabSaver

Returns whether double or single precision is used.

getUseEqualFrequency() - Method in class weka.classifiers.meta.RegressionByDiscretization

Get the value of UseEqualFrequency.

getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.Discretize

Get the value of UseEqualFrequency.

getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Get the value of UseEqualFrequency.

getUseGUI() - Method in class weka.core.Memory

whether to display a dialog in case of a problem (= TRUE) or just print on stderr (= FALSE)

getUseIBk() - Method in class weka.classifiers.rules.DecisionTable

Gets whether IBk is being used instead of the majority class

getUseKernelEstimator() - Method in class weka.classifiers.bayes.NaiveBayes

Gets if kernel estimator is being used.

getUseKononenko() - Method in class weka.filters.supervised.attribute.Discretize

Gets whether Kononenko's MDL criterion is to be used.

getUseLaplace() - Method in class weka.classifiers.trees.J48

Get the value of useLaplace.

getUseLeastValues() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Gets whether to use values with least or most instances

getUseLowerOrder() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Gets whether lower-order terms are used.

getUseMDLcorrection() - Method in class weka.classifiers.rules.PART

Get the value of useMDLcorrection.

getUseMDLcorrection() - Method in class weka.classifiers.trees.J48

Get the value of useMDLcorrection.

getUseMissing() - Method in class weka.filters.unsupervised.attribute.AddNoise

Gets the flag if missing values are treated as extra values.

getUseMutation() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getUseMutation() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getUseNormalization() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns whether normalization is used.

getUseORForMustContainList() - Method in class weka.associations.FPGrowth

Gets whether OR is to be used rather than AND when considering must contain lists.

getUsePairwiseCoupling() - Method in class weka.classifiers.meta.MultiClassClassifier

Gets whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.

getUseProb() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

getUsePropertyIterator() - Method in class weka.experiment.Experiment

Gets whether the custom property iterator should be used.

getUsePruning() - Method in class weka.classifiers.rules.JRip

Gets whether pruning is performed

getUser() - Method in interface weka.core.converters.DatabaseConverter

getUser() - Method in class weka.core.converters.DatabaseLoader

Gets the user name

getUser() - Method in class weka.core.converters.DatabaseSaver

Gets the database user.

getUser() - Method in class weka.gui.sql.ConnectionPanel

returns the current User.

getUser() - Method in class weka.gui.sql.event.ResultChangedEvent

returns the user that produced the table model

getUser() - Method in class weka.gui.sql.ResultSetTable

returns the user that produced the table model

getUser() - Method in class weka.gui.sql.SqlViewer

returns the user from the currently active tab in the ResultPanel, otherwise an empty string.

getUser() - Method in class weka.gui.sql.SqlViewerDialog

returns the chosen user, if any.

getUseRelativePath() - Method in class weka.core.converters.AbstractFileLoader

Gets whether relative paths are to be used

getUseRelativePath() - Method in class weka.core.converters.AbstractFileSaver

Gets whether relative paths are to be used

getUseRelativePath() - Method in interface weka.core.converters.FileSourcedConverter

Gets whether relative paths are to be used

getUseRelativePath() - Method in class weka.gui.beans.SerializedModelSaver

Get whether to use relative paths for the directory.

getUseRelativePaths() - Static method in class weka.gui.experiment.ExperimenterDefaults

whether relative paths are used by default.

getUseResampling() - Method in class weka.classifiers.meta.AdaBoostM1

Get whether resampling is turned on

getUseResampling() - Method in class weka.classifiers.meta.LogitBoost

Get whether resampling is turned on

getUsername() - Method in class weka.experiment.DatabaseUtils

Get the database username.

getUsername() - Method in class weka.gui.DatabaseConnectionDialog

Returns Username from dialog

getUserOptions() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation

returns the options the user supplied for the kernel

getUserOptions() - Method in class weka.core.CheckOptionHandler

Gets the current user-supplied options (creates a copy)

getUseShortIdentifiers() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Get whether short identifiers are to be output.

getUseStars() - Method in class weka.core.Javadoc

whether the Javadoc is prefixed with "*"

getUseStopList() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get whether to ignore all words that are on the stoplist.

getUseStopList() - Method in class weka.classifiers.functions.SGDText

Get whether to ignore all words that are on the stoplist.

getUseStoplist() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets whether if the words on the stoplist are to be ignored (The stoplist is in weka.core.StopWords).

getUseSupervisedDiscretization() - Method in class weka.classifiers.bayes.NaiveBayes

Get whether supervised discretization is to be used.

getUseTab() - Method in class weka.classifiers.evaluation.output.prediction.CSV

Returns whether tab is used as separator.

getUseTabs() - Method in class weka.core.converters.MatlabSaver

Returns whether tabs are used instead of blanks.

getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

getUseTree() - Method in class weka.classifiers.trees.m5.Rule

get whether an m5 tree is being used rather than rules

getUseUnsmoothed() - Method in class weka.classifiers.trees.m5.M5Base

Get whether or not smoothing is being used

getUseWordFrequencies() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Get whether to use word frequencies rather than binary bag of words representation.

getUseWordFrequencies() - Method in class weka.classifiers.functions.SGDText

Get whether to use word frequencies rather than binary bag of words representation.

getV() - Method in class weka.core.matrix.EigenvalueDecomposition

Return the eigenvector matrix

getV() - Method in class weka.core.matrix.SingularValueDecomposition

Return the right singular vectors

getValidating() - Method in class weka.core.xml.XMLDocument

returns whether a validating parser is used.

getValidating() - Method in class weka.core.xml.XMLOptions

returns whether a validating parser is used.

getValidationSetSize() - Method in class weka.classifiers.functions.MultilayerPerceptron

getValidationThreshold() - Method in class weka.classifiers.functions.MultilayerPerceptron

getValue() - Method in class weka.core.json.JSONNode

Returns the stored value.

getValue(Object) - Method in class weka.core.json.JSONNode

Returns the stored value.

getValue() - Method in class weka.core.pmml.FieldMetaInfo.Value

getValue() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Category

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Coefficient

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Constant

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Decision

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.DerivedField

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.EventValues

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Extension

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.FieldValue

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Item

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.MatCell

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.OutputField

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.PairCounts

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.PCovCell

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.PPCell

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.ResultField

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.TimeValue

Gets the value of the value property.

getValue() - Method in class weka.core.pmml.jaxbbindings.Value

Gets the value of the value property.

getValue(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath

returns the value specified by the given path from the object

getValue(Object, String) - Static method in class weka.core.PropertyPath

returns the value specified by the given path from the object

getValue(TechnicalInformation.Field) - Method in class weka.core.TechnicalInformation

returns the value associated with the given field, or empty if field is not currently stored.

getValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Get the value of the new attribute.

getValue(Instance, int) - Static method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Returns either a String object for nominal attributes or a Double for numeric ones.

getValue() - Method in class weka.gui.beans.EnvironmentField

getValue() - Method in class weka.gui.CostMatrixEditor

Gets the cost matrix that is being edited.

getValue() - Method in class weka.gui.GenericArrayEditor

Gets the current object array.

getValue() - Method in class weka.gui.GenericObjectEditor

Gets the current Object.

getValue() - Method in class weka.gui.HierarchyPropertyParser

Get the value of current node

getValue() - Method in class weka.gui.SimpleDateFormatEditor

Gets the date format that is being edited.

getValue() - Method in class weka.gui.SortedTableModel.SortContainer

Returns the value to sort on.

getValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel

returns the value for the cell at columnindex and rowIndex

getValueAt(int, int) - Method in class weka.gui.beans.InteractiveTableModel

getValueAt(int, int) - Method in class weka.gui.SortedTableModel

Returns the value for the cell at columnIndex and rowIndex.

getValueAt(int, int) - Method in class weka.gui.sql.ResultSetTableModel

returns the value for the cell at columnindex and rowIndex.

getValueIndex() - Method in class weka.associations.NominalItem

Get the value index for this item.

getValueIndices() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Get the indices of the indicator values.

getValueName(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns value of a node

getValueRange() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Get the range containing the indicator values.

getValueReplacements() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

getValues(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns array of values of a node

getValues(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

returns array of values of a node

getValues() - Method in class weka.core.pmml.jaxbbindings.DataField

Gets the value of the value property.

getValues() - Method in class weka.core.pmml.TargetMetaInfo

Get the values (discrete case only) for this Target.

getValues() - Method in class weka.core.pmml.VectorInstance

Get the Array of values encapsulated in this vector instance

getValues(InterquartileRange.ValueType) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns the values for the specified type.

getValues() - Method in class weka.gui.visualize.VisualizePanelEvent

getValuesList() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

returns the range for each attribute as string

getVarbValues() - Method in class weka.core.Optimization

Get the variable values.

getVariableNames() - Method in class weka.core.Environment

Get the names of the variables (keys) stored in the internal map.

getVariableValue(String) - Method in class weka.core.Environment

Get the value for a particular variable.

getVariance() - Method in class weka.classifiers.BVDecompose

Get the calculated variance

getVariance() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution

Gets the value of the variance property.

getVariance() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution

Gets the value of the variance property.

getVarianceCovered() - Method in class weka.attributeSelection.PrincipalComponents

Gets the proportion of total variance to account for when retaining principal components

getVarianceCovered() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Gets the proportion of total variance to account for when retaining principal components.

getVector(String) - Method in class weka.core.pmml.VectorDictionary

Gets a vector from the dictionary corresponding to the supplied ID

getVectorDictionary(Element, MiningSchema) - Static method in class weka.core.pmml.VectorDictionary

Returns a new VectorDictionary constructed from the supplied XML container

getVectorFields() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Gets the value of the vectorFields property.

getVectorFields() - Method in class weka.core.pmml.VectorInstance

Get the mining fields that are indexed by this vector instance

getVectorId() - Method in class weka.core.pmml.jaxbbindings.SupportVector

Gets the value of the vectorId property.

getVectorInstance() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Gets the value of the vectorInstance property.

getVectorOfAttrTypes() - Method in class weka.estimators.CheckEstimator.AttrTypes

getVerbose() - Method in class weka.associations.Apriori

Gets whether algorithm is run in verbose mode

getVerificationField() - Method in class weka.core.pmml.jaxbbindings.VerificationFields

Gets the value of the verificationField property.

getVerificationFields() - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Gets the value of the verificationFields property.

getVersion() - Method in class weka.core.pmml.jaxbbindings.Application

Gets the value of the version property.

getVersion() - Method in class weka.core.pmml.jaxbbindings.PMML

Gets the value of the version property.

getVersion() - Method in class weka.core.xml.XMLSerialization

returns the WEKA version with which the serialized object was created

getVisible() - Method in class weka.gui.treevisualizer.Node

Get the value of visible.

getVisibleColCount() - Method in class weka.experiment.ResultMatrix

returns the number of visible columns.

getVisibleRowCount() - Method in class weka.experiment.ResultMatrix

returns the number of visible rows.

getVisual() - Method in class weka.gui.beans.AbstractDataSink

Get the visual being used by this data source.

getVisual() - Method in class weka.gui.beans.AbstractDataSource

Get the visual being used by this data source.

getVisual() - Method in class weka.gui.beans.AbstractEvaluator

Get the visual

getVisual() - Method in class weka.gui.beans.AbstractTestSetProducer

Get the visual for this bean

getVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Get the visual for this bean

getVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer

Get the visual for this bean

getVisual() - Method in class weka.gui.beans.Appender

Get the visual representation

getVisual() - Method in class weka.gui.beans.Associator

Gets the visual appearance of this wrapper bean

getVisual() - Method in class weka.gui.beans.ClassAssigner

getVisual() - Method in class weka.gui.beans.Classifier

Gets the visual appearance of this wrapper bean

getVisual() - Method in class weka.gui.beans.ClassValuePicker

getVisual() - Method in class weka.gui.beans.Clusterer

Gets the visual appearance of this wrapper bean

getVisual() - Method in class weka.gui.beans.CostBenefitAnalysis

getVisual() - Method in class weka.gui.beans.DataVisualizer

Return the visual appearance of this bean

getVisual() - Method in class weka.gui.beans.Filter

Get the visual appearance of this bean

getVisual() - Method in class weka.gui.beans.FlowByExpression

getVisual() - Method in class weka.gui.beans.GraphViewer

Get the visual appearance of this bean

getVisual() - Method in class weka.gui.beans.ImageSaver

getVisual() - Method in class weka.gui.beans.ImageViewer

getVisual() - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Gets the visual appearance of this wrapper bean

getVisual() - Method in class weka.gui.beans.Join

Get the visual for this step

getVisual() - Method in class weka.gui.beans.MetaBean

Gets the visual appearance of this wrapper bean

getVisual() - Method in class weka.gui.beans.ModelPerformanceChart

Return the visual appearance of this bean

getVisual() - Method in class weka.gui.beans.PredictionAppender

Get the visual being used by this data source.

getVisual() - Method in class weka.gui.beans.SerializedModelSaver

Get the visual being used by this data source.

getVisual() - Method in class weka.gui.beans.Sorter

Get the visual representation

getVisual() - Method in class weka.gui.beans.StripChart

Get the visual appearance of this bean

getVisual() - Method in class weka.gui.beans.SubstringLabeler

Get the visual representation

getVisual() - Method in class weka.gui.beans.SubstringReplacer

Get the visual representation

getVisual() - Method in class weka.gui.beans.TextSaver

getVisual() - Method in class weka.gui.beans.TextViewer

Get the visual appearance of this bean

getVisual() - Method in interface weka.gui.beans.Visible

Get the visual representation

getVisualizeMenuItem(AssociationRules, String) - Method in interface weka.gui.visualize.plugins.AssociationRuleVisualizePlugin

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the association rules.

getVisualizeMenuItem(Instances) - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.

getVisualizeMenuItem(String, String) - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the graph in XML BIF format.

getVisualizeMenuItem(String, String) - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the tree in GraphViz's dotty format.

getVisualizeMenuItem(ArrayList<Prediction>, Attribute) - Method in interface weka.gui.visualize.plugins.VisualizePlugin

Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.

getVoteFlag() - Method in class weka.datagenerators.classifiers.classification.RDG1

Gets the vote flag.

getWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated bias according to the Webb definition

getWeight() - Method in class weka.core.pmml.jaxbbindings.Con1

Gets the value of the weight property.

getWeight() - Method in class weka.core.pmml.jaxbbindings.Item

Gets the value of the weight property.

getWeight() - Method in class weka.core.pmml.jaxbbindings.Segment

Gets the value of the weight property.

getWeight() - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Gets the value of the weight property.

getWeightByDistance() - Method in class weka.attributeSelection.ReliefFAttributeEval

Get whether nearest neighbours are being weighted by distance

getWeighted() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Gets the value of the weighted property.

getWeighted() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Gets the value of the weighted property.

getWeightField() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the weightField property.

getWeightingKernel() - Method in class weka.classifiers.lazy.LWL

Gets the kernel weighting method to use.

getWeights() - Method in class weka.classifiers.functions.neural.NeuralNode

call this function to get the weights array.

getWeights() - Method in class weka.classifiers.functions.SGD

getWeights() - Method in class weka.estimators.KernelEstimator

Return the weights of the kernels.

getWeights() - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Get weights

getWeights() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

getWeightThreshold() - Method in class weka.classifiers.meta.AdaBoostM1

Get the degree of weight thresholding

getWeightThreshold() - Method in class weka.classifiers.meta.LogitBoost

Get the degree of weight thresholding

getWeightTrimBeta() - Method in class weka.classifiers.functions.SimpleLogistic

Get the value of weightTrimBeta.

getWeightTrimBeta() - Method in class weka.classifiers.trees.LMT

Get the value of weightTrimBeta.

getWeightTrimBeta() - Method in class weka.classifiers.trees.lmt.LogisticBase

Get the value of weightTrimBeta.

getWidth() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Gets the value of the width property.

getWidth() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the width property.

getWidth() - Method in class weka.core.pmml.jaxbbindings.Neuron

Gets the value of the width property.

getWidth() - Method in class weka.gui.beans.BeanInstance

Gets the width of this bean

getWindow(Class<?>) - Method in class weka.gui.Main

returns the first instance of the given window class, null if none can be found.

getWindow(String) - Method in class weka.gui.Main

returns the first window with the given title, null if none can be found.

getWindowList() - Method in class weka.gui.Main

returns all currently open frames.

getWindowSize() - Method in class weka.classifiers.lazy.IBk

Gets the maximum number of instances allowed in the training pool.

getWindowSize() - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Gets the value of the windowSize property.

getWithPrefix(String) - Method in class weka.core.Trie

returns all stored strings that match the given prefix

getWords() - Method in class weka.core.CheckScheme

returns the words used for assembling strings in a comma-separated list.

getWords() - Method in class weka.core.TestInstances

returns the words used for assembling strings in a comma-separated list.

getWordSeparators() - Method in class weka.core.CheckScheme

returns the word separators (chars) to use for assembling strings.

getWordSeparators() - Method in class weka.core.TestInstances

returns the word separators (chars) to use for assembling strings.

getWordsToKeep() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.

getWrappedAlgorithm() - Method in class weka.gui.beans.Associator

Returns the wrapped associator

getWrappedAlgorithm() - Method in class weka.gui.beans.Classifier

Returns the wrapped classifier

getWrappedAlgorithm() - Method in class weka.gui.beans.Clusterer

Returns the wrapped clusterer

getWrappedAlgorithm() - Method in class weka.gui.beans.Filter

Get the filter wrapped by this bean

getWrappedAlgorithm() - Method in class weka.gui.beans.Loader

Get the loader

getWrappedAlgorithm() - Method in class weka.gui.beans.Saver

Get the saver

getWrappedAlgorithm() - Method in interface weka.gui.beans.WekaWrapper

Get the algorithm

getWrappedRules() - Method in class weka.associations.FilteredAssociationRules

Get the wrapped AssociationRules object.

getWriteMode() - Method in class weka.core.converters.AbstractSaver

Gets the write mode.

getWriteMode() - Method in interface weka.core.converters.Saver

Gets the write mode

getWriter() - Method in class weka.core.converters.AbstractFileSaver

Gets the writer

getWriter(String) - Method in class weka.gui.visualize.PrintableComponent

returns the JComponentWriter associated with the given name, is null if not found.

getWriter(String) - Method in interface weka.gui.visualize.PrintableHandler

returns the JComponentWriter associated with the given name, is null if not found

getWriter(String) - Method in class weka.gui.visualize.PrintablePanel

returns the JComponentWriter associated with the given name, is null if not found

getWriters() - Method in class weka.gui.visualize.PrintableComponent

returns a Hashtable with the current available JComponentWriters in the save dialog.

getWriters() - Method in interface weka.gui.visualize.PrintableHandler

returns a Hashtable with the current available JComponentWriters in the save dialog.

getWriters() - Method in class weka.gui.visualize.PrintablePanel

returns a Hashtable with the current available JComponentWriters in the save dialog.

getWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub

Get the calculated variance according to the Webb definition

getX() - Method in class weka.classifiers.functions.neural.NeuralConnection

getX() - Method in class weka.gui.beans.BeanInstance

Gets the x coordinate of this bean

getXCoordinates() - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Gets the value of the xCoordinates property.

getXCoordinates() - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Gets the value of the xCoordinates property.

getXindex() - Method in class weka.gui.visualize.PlotData2D

Get the currently set x index of the data

getXIndex() - Method in class weka.gui.visualize.VisualizePanel

Get the index of the attribute on the x axis

getXLabelFreq() - Method in class weka.gui.beans.StripChart

Get the frequency by which x axis values are printed

getXMLDocument() - Method in class weka.core.xml.XMLOptions

returns the handler of the XML document.

getXScale() - Method in class weka.gui.visualize.JComponentWriter

returns the scale factor for the x-axis

getXScale() - Method in class weka.gui.visualize.PrintableComponent

returns the scale factor for the x-axis.

getXScale() - Method in interface weka.gui.visualize.PrintableHandler

returns the scale factor for the x-axis

getXScale() - Method in class weka.gui.visualize.PrintablePanel

returns the scale factor for the x-axis

getY() - Method in class weka.classifiers.functions.neural.NeuralConnection

getY() - Method in class weka.gui.beans.BeanInstance

Gets the y coordinate of this bean

getYCoordinates() - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Gets the value of the yCoordinates property.

getYCoordinates() - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Gets the value of the yCoordinates property.

getYindex() - Method in class weka.gui.visualize.PlotData2D

Get the currently set y index of the data

getYIndex() - Method in class weka.gui.visualize.VisualizePanel

Get the index of the attribute on the y axis

getYScale() - Method in class weka.gui.visualize.JComponentWriter

returns the scale factor for the y-axis

getYScale() - Method in class weka.gui.visualize.PrintableComponent

returns the scale factor for the y-axis.

getYScale() - Method in interface weka.gui.visualize.PrintableHandler

returns the scale factor for the y-axis

getYScale() - Method in class weka.gui.visualize.PrintablePanel

returns the scale factor for the y-axis

getZeroThreshold() - Method in class weka.core.pmml.jaxbbindings.VerificationField

Gets the value of the zeroThreshold property.

getZMax() - Method in class weka.classifiers.meta.LogitBoost

Get the Z max threshold on the responses

getZoomSetting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

gini(Map<String, WeightMass>) - Static method in class weka.classifiers.trees.ht.GiniSplitMetric

Return the gini metric computed from the supplied distribution

GINI_SPLIT - Static variable in class weka.classifiers.trees.HoeffdingTree

GiniSplitMetric - Class in weka.classifiers.trees.ht

Implements the gini splitting criterion

GiniSplitMetric() - Constructor for class weka.classifiers.trees.ht.GiniSplitMetric

globalBlendTipText() - Method in class weka.classifiers.lazy.KStar

Returns the tip text for this property

globalInfo() - Method in class weka.associations.Apriori

Returns a string describing this associator

globalInfo() - Method in class weka.associations.FilteredAssociator

Returns a string describing this Associator

globalInfo() - Method in class weka.associations.FPGrowth

Returns a string describing this associator

globalInfo() - Method in class weka.attributeSelection.BestFirst

Returns a string describing this search method

globalInfo() - Method in class weka.attributeSelection.CfsSubsetEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.CorrelationAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.GainRatioAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.GreedyStepwise

Returns a string describing this search method

globalInfo() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.OneRAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.PrincipalComponents

Returns a string describing this attribute transformer

globalInfo() - Method in class weka.attributeSelection.Ranker

Returns a string describing this search method

globalInfo() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.classifiers.bayes.BayesNet

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.NaiveBayes

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.bayes.net.BIFReader

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

This will return a string describing the class.

globalInfo() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.K2

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TAN

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.K2

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

This will return a string describing the search algorithm.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TAN

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.BVDecompose

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.BVDecomposeSegCVSub

Returns a string describing this object

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.CSV

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.HTML

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.Null

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.PlainText

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.XML

Returns a string describing the output generator.

globalInfo() - Method in class weka.classifiers.functions.GaussianProcesses

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.LinearRegression

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.functions.Logistic

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.functions.MultilayerPerceptron

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.functions.SGD

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.SGDText

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.functions.SimpleLogistic

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.SMO

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.SMOreg

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.Puk

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.supportVector.RegSMO

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Returns a string describing the object

globalInfo() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns a string describing the kernel

globalInfo() - Method in class weka.classifiers.functions.VotedPerceptron

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.lazy.IBk

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.lazy.KStar

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.lazy.LWL

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.AdaBoostM1

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.AdditiveRegression

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns a string describing this search method

globalInfo() - Method in class weka.classifiers.meta.Bagging

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.ClassificationViaRegression

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.CostSensitiveClassifier

globalInfo() - Method in class weka.classifiers.meta.CVParameterSelection

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.meta.FilteredClassifier

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.LogitBoost

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.MultiClassClassifier

globalInfo() - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable

globalInfo() - Method in class weka.classifiers.meta.MultiScheme

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.RandomCommittee

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.meta.RandomSubSpace

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.Stacking

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.Vote

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.misc.SerializedClassifier

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.DecisionTable

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.JRip

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.M5Rules

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.OneR

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.PART

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.rules.ZeroR

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.DecisionStump

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.HoeffdingTree

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.J48

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.LMT

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.m5.M5Base

returns information about the classifier

globalInfo() - Method in class weka.classifiers.trees.RandomForest

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.RandomTree

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.trees.REPTree

Returns a string describing classifier

globalInfo() - Method in class weka.clusterers.Canopy

Returns a string describing this clusterer.

globalInfo() - Method in class weka.clusterers.Cobweb

Returns a string describing this clusterer

globalInfo() - Method in class weka.clusterers.EM

Returns a string describing this clusterer

globalInfo() - Method in class weka.clusterers.FarthestFirst

Returns a string describing this clusterer

globalInfo() - Method in class weka.clusterers.FilteredClusterer

Returns a string describing this clusterer.

globalInfo() - Method in class weka.clusterers.HierarchicalClusterer

This will return a string describing the clusterer.

globalInfo() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns a string describing classifier

globalInfo() - Method in class weka.clusterers.SimpleKMeans

Returns a string describing this clusterer.

globalInfo() - Method in class weka.core.ChebyshevDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.converters.ArffLoader

Returns a string describing this Loader

globalInfo() - Method in class weka.core.converters.ArffSaver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.converters.C45Loader

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.core.converters.C45Saver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.converters.CSVLoader

Returns a string describing this attribute evaluator.

globalInfo() - Method in class weka.core.converters.CSVSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.DatabaseLoader

Returns a string describing this Loader

globalInfo() - Method in class weka.core.converters.DatabaseSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.JSONLoader

Returns a string describing this Loader.

globalInfo() - Method in class weka.core.converters.JSONSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.LibSVMLoader

Returns a string describing this Loader.

globalInfo() - Method in class weka.core.converters.LibSVMSaver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.converters.MatlabLoader

Returns a string describing this Loader.

globalInfo() - Method in class weka.core.converters.MatlabSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.SerializedInstancesLoader

Returns a string describing this object

globalInfo() - Method in class weka.core.converters.SerializedInstancesSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.SVMLightLoader

Returns a string describing this Loader.

globalInfo() - Method in class weka.core.converters.SVMLightSaver

Returns a string describing this Saver.

globalInfo() - Method in class weka.core.converters.TextDirectoryLoader

Returns a string describing this loader

globalInfo() - Method in class weka.core.converters.XRFFLoader

Returns a string describing this Loader

globalInfo() - Method in class weka.core.converters.XRFFSaver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.EuclideanDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.ManhattanDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.MinkowskiDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.neighboursearch.BallTree

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Returns a string describing this object.

globalInfo() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.CoverTree

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.KDTree

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.LinearNNSearch

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.NormalizableDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.stemmers.IteratedLovinsStemmer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.stemmers.LovinsStemmer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.stemmers.NullStemmer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.stemmers.SnowballStemmer

Returns a string describing the stemmer.

globalInfo() - Method in class weka.core.tokenizers.AlphabeticTokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.tokenizers.NGramTokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.tokenizers.Tokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.tokenizers.WordTokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.classification.LED24

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.regression.Expression

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.ClusterDefinition

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns a string describing this data generator.

globalInfo() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns a string describing this data generator.

globalInfo() - Method in class weka.experiment.AveragingResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.ClassifierSplitEvaluator

Returns a string describing this split evaluator

globalInfo() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns a string describing this split evaluator

globalInfo() - Method in class weka.experiment.CrossValidationResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.CrossValidationSplitResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.CSVResultListener

Returns a string describing this result listener

globalInfo() - Method in class weka.experiment.DatabaseResultListener

Returns a string describing this result listener

globalInfo() - Method in class weka.experiment.DatabaseResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns a string describing this split evaluator

globalInfo() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns a string describing this result producer.

globalInfo() - Method in class weka.experiment.InstancesResultListener

Returns a string describing this result listener

globalInfo() - Method in class weka.experiment.LearningRateResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.RandomSplitResultProducer

Returns a string describing this result producer

globalInfo() - Method in class weka.experiment.RegressionSplitEvaluator

Returns a string describing this split evaluator

globalInfo() - Method in class weka.experiment.ResultMatrix

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixCSV

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixGnuPlot

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixHTML

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixLatex

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixPlainText

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixSignificance

Returns a string describing the matrix.

globalInfo() - Method in class weka.filters.AllFilter

Returns a string describing this filter

globalInfo() - Method in class weka.filters.MultiFilter

Returns a string describing this filter

globalInfo() - Method in class weka.filters.SimpleFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.supervised.attribute.AddClassification

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.supervised.attribute.AttributeSelection

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.attribute.ClassOrder

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.attribute.Discretize

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.supervised.attribute.NominalToBinary

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.attribute.PartitionMembership

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.instance.Resample

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns a string describing this filter

globalInfo() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Add

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddID

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddUserFields

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Center

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Copy

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Discretize

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

globalInfo() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToString

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToBinary

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.Obfuscate

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.Remove

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Global help info

globalInfo() - Method in class weka.filters.unsupervised.attribute.Reorder

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.Standardize

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SwapValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Returns a string describing this classifier

globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Returns a string describing this classifier

globalInfo() - Method in class weka.filters.unsupervised.attribute.Transpose

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.Randomize

Returns a string describing this classifier

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns a string describing this classifier

globalInfo() - Method in class weka.filters.unsupervised.instance.Resample

Returns a string describing this classifier

globalInfo() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Returns a string describing this filter.

globalInfo() - Method in class weka.gui.beans.Associator

Global info (if it exists) for the wrapped classifier

globalInfo() - Method in class weka.gui.beans.AttributeSummarizer

Global info for this bean

globalInfo() - Method in class weka.gui.beans.ClassAssigner

Global info for this bean

globalInfo() - Method in class weka.gui.beans.Classifier

Global info (if it exists) for the wrapped classifier

globalInfo() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Global info for this bean

globalInfo() - Method in class weka.gui.beans.ClassValuePicker

Global info for this bean

globalInfo() - Method in class weka.gui.beans.Clusterer

Global info (if it exists) for the wrapped classifier

globalInfo() - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Global info for this bean

globalInfo() - Method in class weka.gui.beans.CostBenefitAnalysis

Global info for this bean

globalInfo() - Method in class weka.gui.beans.CrossValidationFoldMaker

Global info for this bean

globalInfo() - Method in class weka.gui.beans.DataVisualizer

Global info for this bean

globalInfo() - Method in class weka.gui.beans.Filter

Global info (if it exists) for the wrapped filter

globalInfo() - Method in class weka.gui.beans.FlowByExpression

globalInfo() - Method in class weka.gui.beans.GraphViewer

Global info for this bean

globalInfo() - Method in class weka.gui.beans.ImageSaver

Global info for this bean

globalInfo() - Method in class weka.gui.beans.ImageViewer

Global info for this bean

globalInfo() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Global info for this bean

globalInfo() - Method in class weka.gui.beans.Join

Global info for the method

globalInfo() - Method in class weka.gui.beans.Loader

Global info (if it exists) for the wrapped loader

globalInfo() - Method in class weka.gui.beans.ModelPerformanceChart

Global info for this bean

globalInfo() - Method in class weka.gui.beans.PredictionAppender

Global description of this bean

globalInfo() - Method in class weka.gui.beans.Saver

Global info (if it exists) for the wrapped loader

globalInfo() - Method in class weka.gui.beans.ScatterPlotMatrix

Global info for this bean

globalInfo() - Method in class weka.gui.beans.SerializedModelSaver

Global info for this bean.

globalInfo() - Method in class weka.gui.beans.Sorter

Help information suitable for displaying in the GUI.

globalInfo() - Method in class weka.gui.beans.StripChart

Global info for this bean

globalInfo() - Method in class weka.gui.beans.SubstringLabeler

Help information suitable for displaying in the GUI.

globalInfo() - Method in class weka.gui.beans.SubstringReplacer

About information

globalInfo() - Method in class weka.gui.beans.TestSetMaker

Global info for this bean

globalInfo() - Method in class weka.gui.beans.TextSaver

Global info for this bean

globalInfo() - Method in class weka.gui.beans.TextViewer

Global info for this bean

globalInfo() - Method in class weka.gui.beans.TrainingSetMaker

Global info for this bean

globalInfo() - Method in class weka.gui.beans.TrainTestSplitMaker

Global info for this bean

globalInfo() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Returns a string describing this tool

GLOBALINFO_ENDTAG - Static variable in class weka.core.GlobalInfoJavadoc

the end comment tag for inserting the generated Javadoc

GLOBALINFO_METHOD - Static variable in class weka.core.GlobalInfoJavadoc

the globalInfo method name

GLOBALINFO_STARTTAG - Static variable in class weka.core.GlobalInfoJavadoc

the start comment tag for inserting the generated Javadoc

GlobalInfoJavadoc - Class in weka.core

Generates Javadoc comments from the class's globalInfo method.

GlobalInfoJavadoc() - Constructor for class weka.core.GlobalInfoJavadoc

default constructor

GlobalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.global

This Bayes Network learning algorithm uses cross validation to estimate classification accuracy.

GlobalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

goDown(String) - Method in class weka.gui.HierarchyPropertyParser

Go to a certain node of the tree down from the current node according to the specified relative path.

GOECustomizer - Interface in weka.gui.beans

Extends BeanCustomizer.

goTo(String) - Method in class weka.gui.HierarchyPropertyParser

Go to a certain node of the tree according to the specified path Note that the path must be absolute path from the root.

goToChild(String) - Method in class weka.gui.HierarchyPropertyParser

Go to one child node from the current position in the tree according to the given value
If the child node with the given value cannot be found it returns false, true otherwise.

goToChild(int) - Method in class weka.gui.HierarchyPropertyParser

Go to one child node from the current position in the tree according to the given position

goToParent() - Method in class weka.gui.HierarchyPropertyParser

Go to the parent from the current position in the tree If the current position is the root, it stays there and does not move

goToRoot() - Method in class weka.gui.HierarchyPropertyParser

Go to the root of the tree

gr(double, double) - Static method in class weka.core.Utils

Tests if a is greater than b.

gracePeriodTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

graph(FPGrowth.FPTreeRoot) - Method in class weka.associations.FPGrowth

Assemble a dot graph representation of the FP-tree.

graph() - Method in class weka.classifiers.bayes.BayesNet

Returns a BayesNet graph in XMLBIF ver 0.3 format.

graph() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns graph describing the classifier (if possible).

graph() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns graph describing the classifier (if possible).

graph() - Method in class weka.classifiers.meta.CVParameterSelection

Returns graph describing the classifier (if possible).

graph() - Method in class weka.classifiers.meta.FilteredClassifier

Returns graph describing the classifier (if possible).

graph() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns graph describing the classifier (if possible).

graph() - Method in class weka.classifiers.pmml.consumer.TreeModel

graph() - Method in class weka.classifiers.trees.HoeffdingTree

graph() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns graph describing the tree.

graph() - Method in class weka.classifiers.trees.J48

Returns graph describing the tree.

graph() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree

Returns graph describing the tree.

graph() - Method in class weka.classifiers.trees.LMT

Returns graph describing the tree.

graph() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns graph describing the tree.

graph(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode

Assign a unique identifier to each node in the tree and then calls graphTree

graph() - Method in class weka.classifiers.trees.M5P

Return a dot style String describing the tree.

graph() - Method in class weka.classifiers.trees.RandomTree

Returns graph describing the tree.

graph() - Method in class weka.classifiers.trees.REPTree

Outputs the decision tree as a graph

graph() - Method in class weka.clusterers.Cobweb

Generates the graph string of the Cobweb tree

graph() - Method in class weka.clusterers.HierarchicalClusterer

graph() - Method in interface weka.core.Drawable

Returns a string that describes a graph representing the object.

GraphConstants - Interface in weka.gui.graphvisualizer

GraphConstants.java

GraphEdge - Class in weka.gui.graphvisualizer

This class represents an edge in the graph

GraphEdge(int, int, int) - Constructor for class weka.gui.graphvisualizer.GraphEdge

GraphEdge(int, int, int, String, String) - Constructor for class weka.gui.graphvisualizer.GraphEdge

GraphEvent - Class in weka.gui.beans

Event for graphs

GraphEvent(Object, String, String, int) - Constructor for class weka.gui.beans.GraphEvent

Creates a new GraphEvent instance.

GraphListener - Interface in weka.gui.beans

Describe interface TextListener here.

GraphNode - Class in weka.gui.graphvisualizer

This class represents a node in the Graph.

GraphNode(String, String) - Constructor for class weka.gui.graphvisualizer.GraphNode

Constructor

GraphNode(String, String, int) - Constructor for class weka.gui.graphvisualizer.GraphNode

Constructor

graphTree(StringBuffer) - Method in class weka.classifiers.trees.ht.HNode

graphTree(StringBuffer) - Method in class weka.classifiers.trees.ht.SplitNode

graphType() - Method in class weka.classifiers.bayes.BayesNet

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.meta.CVParameterSelection

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.meta.FilteredClassifier

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.pmml.consumer.TreeModel

graphType() - Method in class weka.classifiers.trees.HoeffdingTree

graphType() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.trees.J48

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.trees.LMT

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.trees.M5P

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.trees.RandomTree

Returns the type of graph this classifier represents.

graphType() - Method in class weka.classifiers.trees.REPTree

Returns the type of graph this classifier represents.

graphType() - Method in class weka.clusterers.Cobweb

Returns the type of graphs this class represents

graphType() - Method in class weka.clusterers.HierarchicalClusterer

graphType() - Method in interface weka.core.Drawable

Returns the type of graph representing the object.

GraphViewer - Class in weka.gui.beans

A bean encapsulating weka.gui.treevisualize.TreeVisualizer

GraphViewer() - Constructor for class weka.gui.beans.GraphViewer

GraphViewerBeanInfo - Class in weka.gui.beans

Bean info class for the graph viewer

GraphViewerBeanInfo() - Constructor for class weka.gui.beans.GraphViewerBeanInfo

GraphVisualizePlugin - Interface in weka.gui.visualize.plugins

Interface implemented by classes loaded dynamically to visualize graphs in the explorer.

GraphVisualizer - Class in weka.gui.graphvisualizer

This class displays the graph we want to visualize.

GraphVisualizer() - Constructor for class weka.gui.graphvisualizer.GraphVisualizer

Constructor
Sets up the gui and initializes all the other previously uninitialized variables.

GreedyStepwise - Class in weka.attributeSelection

GreedyStepwise :

Performs a greedy forward or backward search through the space of attribute subsets.

GreedyStepwise() - Constructor for class weka.attributeSelection.GreedyStepwise

Constructor

GRID - Static variable in class weka.datagenerators.clusterers.BIRCHCluster

Constant set for choice of pattern.

Groovy - Class in weka.core.scripting

A helper class for Groovy.

Groovy() - Constructor for class weka.core.scripting.Groovy

default constructor, tries to instantiate a Groovy classloader.

GroovyPanel - Class in weka.gui.scripting

A scripting panel for Groovy.

GroovyPanel() - Constructor for class weka.gui.scripting.GroovyPanel

GroovyScript - Class in weka.gui.scripting

Represents a Groovy script.

GroovyScript() - Constructor for class weka.gui.scripting.GroovyScript

Initializes the script.

GroovyScript(Document) - Constructor for class weka.gui.scripting.GroovyScript

Initializes the script.

GroovyScript(Document, File) - Constructor for class weka.gui.scripting.GroovyScript

Initializes the script.

GroovyScript.GroovyThread - Class in weka.gui.scripting

Executes a Groovy script in a thread.

GroovyScript.GroovyThread(Script, String[]) - Constructor for class weka.gui.scripting.GroovyScript.GroovyThread

Initializes the thread.

grOrEq(double, double) - Static method in class weka.core.Utils

Tests if a is greater or equal to b.

grouping(boolean) - Method in class weka.core.matrix.FlexibleDecimalFormat

grow(Instances) - Method in class weka.classifiers.rules.JRip.RipperRule

Build one rule using the growing data

grow(Instances) - Method in class weka.classifiers.rules.Rule

Build this rule

GT - Static variable in interface weka.core.mathematicalexpression.sym

GT - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

GUI - Class in weka.classifiers.bayes.net

GUI interface to Bayesian Networks.

GUI() - Constructor for class weka.classifiers.bayes.net.GUI

Constructor
Sets up the gui and initializes all the other previously uninitialized variables.

GUI_MDI - Static variable in class weka.gui.Main

displays the GUI as MDI.

GUI_SDI - Static variable in class weka.gui.Main

displays the GUI as SDI.

GUIChooser - Class in weka.gui

The main class for the Weka GUIChooser.

GUIChooser() - Constructor for class weka.gui.GUIChooser

Creates the experiment environment gui with no initial experiment

GUIChooser.ChildFrameSDI - Class in weka.gui

Specialized JFrame class.

GUIChooser.ChildFrameSDI(GUIChooser, String) - Constructor for class weka.gui.GUIChooser.ChildFrameSDI

constructs a new internal frame that knows about its parent.

GUIChooser.GUIChooserMenuPlugin - Interface in weka.gui

Interface for plugin components that can be accessed from either the Visualization or Tools menu.

GUIChooser.GUIChooserMenuPlugin.Menu - Enum in weka.gui

Enum listing possible menus that plugins can appear in

GUIEDITORS_PROPERTY_FILE - Static variable in class weka.gui.GenericObjectEditor

the properties files containing the class/editor mappings.

GUITipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

H

handles(Capabilities.Capability) - Method in class weka.core.Capabilities: returns true if the classifier handler has the specified capability
handles(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: returns true if the given capability can be handled.
hasAdditional() - Method in class weka.core.TechnicalInformation: returns true if there are further technical informations stored in this
hasAdditional() - Method in class weka.gui.scripting.event.ScriptExecutionEvent: Returns whether additional information is available.
hasAntds() - Method in class weka.classifiers.rules.JRip.RipperRule: Whether this rule has antecedents, i.e.
hasAntds() - Method in class weka.classifiers.rules.Rule: Whether this rule has antecedents, i.e.
hasChild(String) - Method in class weka.core.json.JSONNode: Checks whether the node has a child with the given name.
hasClasspathProblems() - Method in class weka.core.CheckScheme: returns TRUE if the classifier returned a "not in classpath" Exception
hasClasspathProblems() - Method in class weka.estimators.CheckEstimator: returns TRUE if the estimator returned a "not in classpath" Exception
hasDependencies() - Method in class weka.core.Capabilities: Checks whether there are any dependencies at all
hasDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: returns true if the classifier handler has a dependency for the specified capability
hasEmptyRow() - Method in class weka.gui.beans.InteractiveTableModel: Returns true if the model has an empty row
hash - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: attribute value hash code
hashCode() - Method in class weka.associations.BinaryItem
hashCode() - Method in class weka.associations.Item
hashCode() - Method in class weka.associations.ItemSet: Produces a hash code for a item set.
hashCode() - Method in class weka.classifiers.rules.DecisionTableHashKey: Calculates a hash code
hashCode() - Method in class weka.core.SerializedObject: Returns a hashcode for this object.
hashCode() - Method in class weka.core.Trie: Returns the hash code value for this collection.
hasIncomingBatchInstances() - Method in class weka.gui.beans.Classifier: Returns true if this classifier has an incoming connection that is a batch set of instances
hasIncomingBatchInstances() - Method in class weka.gui.beans.Clusterer: Returns true if this clusterer has an incoming connection that is a batch set of instances
hasIncomingStreamInstances() - Method in class weka.gui.beans.Classifier: Returns true if this classifier has an incoming connection that is an instance stream
hasIndex() - Method in class weka.core.PropertyPath.PathElement: returns whether the property is an index-based one
hasInterface(String, String) - Static method in class weka.core.ClassDiscovery: Checks whether the given class implements the given interface.
hasInterface(Class<?>, Class<?>) - Static method in class weka.core.ClassDiscovery: Checks whether the given class implements the given interface.
hasMaxRows() - Method in class weka.gui.sql.ResultSetHelper: whether a limit on the rows to retrieve was set.
hasMissingValue() - Method in class weka.core.AbstractInstance: Tests whether an instance has a missing value.
hasMissingValue() - Method in interface weka.core.Instance: Tests whether an instance has a missing value.
hasModels() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
hasMoreElements(Instances) - Method in class weka.core.converters.ConverterUtils.DataSource: returns whether there are more Instance objects in the data.
hasMoreElements() - Method in class weka.core.tokenizers.AlphabeticTokenizer: returns whether there are more elements still
hasMoreElements() - Method in class weka.core.tokenizers.NGramTokenizer: returns true if there's more elements available
hasMoreElements() - Method in class weka.core.tokenizers.Tokenizer: Tests if this enumeration contains more elements.
hasMoreElements() - Method in class weka.core.tokenizers.WordTokenizer: Tests if this enumeration contains more elements.
hasMoreElements() - Method in class weka.core.WekaEnumeration: Tests if there are any more elements to enumerate.
hasMoreIterations() - Method in class weka.experiment.Experiment: Returns true if there are more iterations to carry out in the experiment.
hasNext() - Method in class weka.core.Trie.TrieIterator: Returns true if the iteration has more elements.
hasResult() - Method in class weka.gui.sql.event.QueryExecuteEvent: whether a ResultSet was produced, e.g.
hasTargetMetaData() - Method in class weka.core.pmml.MiningSchema: Returns true if there is Target meta data.
hasUID(String) - Static method in class weka.core.SerializationHelper: checks whether the given class contains a serialVersionUID.
hasUID(Class<?>) - Static method in class weka.core.SerializationHelper: checks whether the given class contains a serialVersionUID.
hasZeropoint() - Method in class weka.core.Attribute: Returns whether the attribute has a zeropoint and may be added meaningfully.
HEADER - Static variable in class weka.core.json.JSONInstances: the header section.
Header - Class in weka.core.pmml.jaxbbindings: Java class for Header element declaration.
Header() - Constructor for class weka.core.pmml.jaxbbindings.Header
HEADER - Static variable in class weka.core.RepositoryIndexGenerator
header(int) - Method in class weka.experiment.PairedTTester: Creates a "header" string describing the current resultsets.
header(int) - Method in interface weka.experiment.Tester: Creates a "header" string describing the current resultsets.
headerKeys() - Method in class weka.experiment.ResultMatrix: returns an enumeration of the header keys.
HeadlessEventCollector - Interface in weka.gui.beans: Interface for Knowledge Flow components that (typically) provide an interactive graphical visualization to implement.
HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: default height
HEIGHT - Static variable in class weka.gui.sql.SqlViewer: the height property in the history file.
heuristicStopTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
hiddenLayersTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
HierarchicalBCEngine - Class in weka.gui.graphvisualizer: This class lays out the vertices of a graph in a hierarchy of vertical levels, with a number of nodes in each level.
HierarchicalBCEngine(ArrayList<GraphNode>, ArrayList<GraphEdge>, int, int) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: Constructor - takes in FastVectors of nodes and edges, and the initial width and height of a node
HierarchicalBCEngine(ArrayList<GraphNode>, ArrayList<GraphEdge>, int, int, boolean) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: Constructor - takes in FastVectors of nodes and edges, the initial width and height of a node, and a boolean value to indicate if the edges should be concentrated.
HierarchicalBCEngine() - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: SimpleConstructor If we want to instantiate the class first, and if information for nodes and edges is not available.
HierarchicalClusterer - Class in weka.clusterers: Hierarchical clustering class.
HierarchicalClusterer() - Constructor for class weka.clusterers.HierarchicalClusterer
HierarchyPropertyParser - Class in weka.gui: This class implements a parser to read properties that have a hierarchy(i.e.
HierarchyPropertyParser() - Constructor for class weka.gui.HierarchyPropertyParser: Default constructor
HierarchyPropertyParser(String, String) - Constructor for class weka.gui.HierarchyPropertyParser: Constructor that builds a tree from the given property with the given delimitor
HierarchyVisualizer - Class in weka.gui.hierarchyvisualizer
HierarchyVisualizer(String) - Constructor for class weka.gui.hierarchyvisualizer.HierarchyVisualizer
highlightLastRow(int) - Method in class weka.gui.beans.InteractiveTablePanel: Highlight the last row in the table
HillClimber - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.HillClimber
HillClimber - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.HillClimber
HINGE - Static variable in class weka.classifiers.functions.SGD: the hinge loss function.
HINGE - Static variable in class weka.classifiers.functions.SGDText: the hinge loss function.
HISTORY_NAME - Static variable in class weka.gui.sql.ConnectionPanel: the name of the history.
HISTORY_NAME - Static variable in class weka.gui.sql.QueryPanel: the name of the history.
historyChanged(HistoryChangedEvent) - Method in interface weka.gui.sql.event.HistoryChangedListener: This method gets called when a history is modified.
historyChanged(HistoryChangedEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when a history is modified.
HistoryChangedEvent - Class in weka.gui.sql.event: An event that is generated when a history is modified.
HistoryChangedEvent(Object, String, DefaultListModel) - Constructor for class weka.gui.sql.event.HistoryChangedEvent: constructs the event
HistoryChangedListener - Interface in weka.gui.sql.event: A listener for changes in a history.
historySelected(GenericObjectEditorHistory.HistorySelectionEvent) - Method in interface weka.gui.GenericObjectEditorHistory.HistorySelectionListener: Gets called when a history item gets selected.
hit(Rectangle, Shape, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
HLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
HNode - Class in weka.classifiers.trees.ht: Abstract base class for nodes in a Hoeffding tree
HNode() - Constructor for class weka.classifiers.trees.ht.HNode: Construct a new HNode
HNode(Map<String, WeightMass>) - Constructor for class weka.classifiers.trees.ht.HNode: Construct a new HNode with the supplied class distribution
hoeffdingTieThresholdTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
HoeffdingTree - Class in weka.classifiers.trees: A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not change over time.
HoeffdingTree() - Constructor for class weka.classifiers.trees.HoeffdingTree
HoldOutSubsetEvaluator - Class in weka.attributeSelection: Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
HoldOutSubsetEvaluator() - Constructor for class weka.attributeSelection.HoldOutSubsetEvaluator
HostListPanel - Class in weka.gui.experiment: This panel controls setting a list of hosts for a RemoteExperiment to use.
HostListPanel(RemoteExperiment) - Constructor for class weka.gui.experiment.HostListPanel: Creates the host list panel with the given experiment.
HostListPanel() - Constructor for class weka.gui.experiment.HostListPanel: Create the host list panel initially disabled.
HTML - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions in HTML.
HTML() - Constructor for class weka.classifiers.evaluation.output.prediction.HTML
HUBER - Static variable in class weka.classifiers.functions.SGD: The Huber loss function
hypot(double, double) - Static method in class weka.core.matrix.Maths: sqrt(a^2 + b^2) without under/overflow.

I

I0 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

I0a - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

I0b - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

I1 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

I2 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

I3 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved

IBk - Class in weka.classifiers.lazy

K-nearest neighbours classifier.

IBk(int) - Constructor for class weka.classifiers.lazy.IBk

IBk classifier.

IBk() - Constructor for class weka.classifiers.lazy.IBk

IB1 classifer.

ICON_PATH - Static variable in class weka.gui.beans.BeanVisual

ICSSearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci

This Bayes Network learning algorithm uses conditional independence tests to find a skeleton, finds V-nodes and applies a set of rules to find the directions of the remaining arrows.

ICSSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

ID - Variable in class weka.gui.graphvisualizer.GraphNode

ID and label for the node

identity(int, int) - Static method in class weka.core.matrix.Matrix

Generate identity matrix

IDFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

IDIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddID

Returns the tip text for this property

IDLE - Static variable in class weka.gui.beans.BeanInstance

class variable holding all the beans

IFELSE - Static variable in interface weka.core.mathematicalexpression.sym

ignoreCaseForNamesTipText() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the tip text for this property

ignoreCaseTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Returns the tip text for this property

ignoreClassTipText() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Returns the tip text for this property

ignored() - Method in class weka.core.xml.PropertyHandler

returns an enumeration of the stored display names and classes of properties to ignore.
NOTE: String and Class Objects are mixed in this enumeration, depending whether it is a global property to ignore or just one for a certain class!

ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns the tip text for this property.

ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns the tip text for this property

ignoreRangeTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns the tip text for this property

ImageEvent - Class in weka.gui.beans

Event that encapsulates an Image

ImageEvent(Object, BufferedImage) - Constructor for class weka.gui.beans.ImageEvent

Construct a new ImageEvent

ImageEvent(Object, BufferedImage, String) - Constructor for class weka.gui.beans.ImageEvent

Construct an ImageEvent

ImageListener - Interface in weka.gui.beans

Interface to something that can process an ImageEvent

IMAGES - Static variable in class weka.gui.ComponentHelper

the default directories for images

IMAGES_DIR - Static variable in class weka.gui.scripting.FileScriptingPanel

the directory with the scripting-specific images.

ImageSaver - Class in weka.gui.beans

Component that can accept ImageEvents and save their encapsulated images to a file.

ImageSaver() - Constructor for class weka.gui.beans.ImageSaver

Constructs a new ImageSaver

ImageSaverBeanInfo - Class in weka.gui.beans

BeanInfo class for the ImageSaver component.

ImageSaverBeanInfo() - Constructor for class weka.gui.beans.ImageSaverBeanInfo

ImageSaverCustomizer - Class in weka.gui.beans

Customizer for the ImageSaver component.

ImageSaverCustomizer() - Constructor for class weka.gui.beans.ImageSaverCustomizer

Constructor

ImageViewer - Class in weka.gui.beans

A KF component that can accept imageEvent connections in order to display static images in a popup window

ImageViewer() - Constructor for class weka.gui.beans.ImageViewer

Constructs a new ImageViewer

ImageViewerBeanInfo - Class in weka.gui.beans

BeanInfo class for the ImageViewer component

ImageViewerBeanInfo() - Constructor for class weka.gui.beans.ImageViewerBeanInfo

Impurity - Class in weka.classifiers.trees.m5

Class for handling the impurity values when spliting the instances

Impurity(int, int, Instances, int) - Constructor for class weka.classifiers.trees.m5.Impurity

Constructs an Impurity object containing the impurity values of partitioning the instances using an attribute

InactiveHNode - Class in weka.classifiers.trees.ht

Class implementing an inactive node (i.e.

InactiveHNode(Map<String, WeightMass>) - Constructor for class weka.classifiers.trees.ht.InactiveHNode

Constructor

includeClassTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

incomingInstanceToVectorFieldVals(double[]) - Method in class weka.core.pmml.VectorDictionary

Convert an incoming instance to an array of values that corresponds to the fields referenced by the support vectors in the vector dictionary

incompleteBeta(double, double, double) - Static method in class weka.core.Statistics

Returns the Incomplete Beta Function evaluated from zero to xx.

incompleteBetaFraction1(double, double, double) - Static method in class weka.core.Statistics

Continued fraction expansion #1 for incomplete beta integral.

incompleteBetaFraction2(double, double, double) - Static method in class weka.core.Statistics

Continued fraction expansion #2 for incomplete beta integral.

incompleteGamma(double, double) - Static method in class weka.core.Statistics

Returns the Incomplete Gamma function.

incompleteGammaComplement(double, double) - Static method in class weka.core.Statistics

Returns the Complemented Incomplete Gamma function.

incorrect() - Method in class weka.classifiers.evaluation.ConfusionMatrix

Gets the number of incorrect classifications (that is, for which an incorrect prediction was made).

incorrect() - Method in class weka.classifiers.evaluation.Evaluation

Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).

incorrect() - Method in class weka.classifiers.Evaluation

Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).

incrCoordCount() - Method in class weka.core.neighboursearch.PerformanceStats

Increments the coordinate count (number of coordinates/attributes looked at).

increaseFontSize() - Method in class weka.gui.beans.Note

Increase the font size by one

increaseFrequency(int) - Method in class weka.associations.Item

Increase the frequency of this item.

increaseFrequency() - Method in class weka.associations.Item

Increment the frequency of this item.

incremental(double, int) - Method in class weka.classifiers.trees.m5.Impurity

Incrementally computes the impurirty values

INCREMENTAL - Static variable in interface weka.core.converters.Loader

INCREMENTAL - Static variable in interface weka.core.converters.Saver

IncrementalClassifierEvaluator - Class in weka.gui.beans

Bean that evaluates incremental classifiers

IncrementalClassifierEvaluator() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluator

IncrementalClassifierEvaluatorBeanInfo - Class in weka.gui.beans

Bean info class for the incremental classifier evaluator bean

IncrementalClassifierEvaluatorBeanInfo() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo

IncrementalClassifierEvaluatorCustomizer - Class in weka.gui.beans

GUI Customizer for the incremental classifier evaluator bean

IncrementalClassifierEvaluatorCustomizer() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

IncrementalClassifierEvent - Class in weka.gui.beans

Class encapsulating an incrementally built classifier and current instance

IncrementalClassifierEvent(Object, Classifier, Instance, int) - Constructor for class weka.gui.beans.IncrementalClassifierEvent

Creates a new IncrementalClassifierEvent instance.

IncrementalClassifierEvent(Object, Classifier, Instances) - Constructor for class weka.gui.beans.IncrementalClassifierEvent

Creates a new incremental classifier event that encapsulates header information and classifier.

IncrementalClassifierEvent(Object) - Constructor for class weka.gui.beans.IncrementalClassifierEvent

IncrementalClassifierListener - Interface in weka.gui.beans

Interface to something that can process a IncrementalClassifierEvent

IncrementalConverter - Interface in weka.core.converters

Marker interface for a loader/saver that can retrieve instances incrementally

IncrementalEstimator - Interface in weka.estimators

Interface for an incremental probability estimators.

incrIntNodeCount() - Method in class weka.core.neighboursearch.TreePerformanceStats

Increments the internal node count.

incrLeafCount() - Method in class weka.core.neighboursearch.TreePerformanceStats

Increments the leaf count.

incrPointCount() - Method in class weka.core.neighboursearch.PerformanceStats

Increments the point count (number of datapoints looked at).

index() - Method in class weka.core.Attribute

Returns the index of this attribute.

index(int) - Method in class weka.core.DenseInstance

Returns the index of the attribute stored at the given position.

index(int) - Method in interface weka.core.Instance

Returns the index of the attribute stored at the given position in the sparse representation.

index(int) - Method in class weka.core.pmml.Array

Returns the index of the value stored at the given position

index(int) - Method in class weka.core.pmml.SparseArray

Returns the index of the value stored at the given position

index(int) - Method in class weka.core.SparseInstance

Returns the index of the attribute stored at the given position.

INDEX_BEANCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans

the index in the Vector, where the BeanConnections are stored (Instances and Connections are stored in a Vector and then serialized)

INDEX_BEANINSTANCES - Static variable in class weka.gui.beans.xml.XMLBeans

the index in the Vector, where the BeanInstances are stored (Instances and Connections are stored in a Vector and then serialized)

indexOf(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Searches for the first occurrence of elem.

indexOf(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Searches for the first occurrence of elem, beginning the search at index.

indexOfMax() - Method in class weka.core.matrix.DoubleVector

Returns the index of the maximum.

indexOfValue(String) - Method in class weka.core.Attribute

Returns the index of a given attribute value.

indexToString(int) - Static method in class weka.core.SingleIndex

Creates a string representation of the given index.

indicesToRangeList(int[]) - Static method in class weka.core.Range

Creates a string representation of the indices in the supplied array.

individualPredictions(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier

Returns the individual predictions of the base classifiers for an instance.

INFO - Static variable in class weka.core.Debug

the log level Info

info(int[]) - Static method in class weka.core.Utils

Computes entropy for an array of integers.

INFO_GAIN_SPLIT - Static variable in class weka.classifiers.trees.HoeffdingTree

infoGain() - Method in class weka.classifiers.trees.j48.BinC45Split

Returns (C4.5-type) information gain for the generated split.

infoGain() - Method in class weka.classifiers.trees.j48.C45Split

Returns (C4.5-type) information gain for the generated split.

InfoGainAttributeEval - Class in weka.attributeSelection

InfoGainAttributeEval :

Evaluates the worth of an attribute by measuring the information gain with respect to the class.

InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute).

Valid options are:

InfoGainAttributeEval() - Constructor for class weka.attributeSelection.InfoGainAttributeEval

Constructor

InfoGainSplitCrit - Class in weka.classifiers.trees.j48

Class for computing the information gain for a given distribution.

InfoGainSplitCrit() - Constructor for class weka.classifiers.trees.j48.InfoGainSplitCrit

InfoGainSplitMetric - Class in weka.classifiers.trees.ht

Implements the info gain splitting criterion

InfoGainSplitMetric(double) - Constructor for class weka.classifiers.trees.ht.InfoGainSplitMetric

InfoPanel - Class in weka.gui.sql

A simple panel for displaying information, e.g.

InfoPanel(JFrame) - Constructor for class weka.gui.sql.InfoPanel

creates the panel

InfoPanelCellRenderer - Class in weka.gui.sql

A specialized renderer that takes care of JLabels in a JList.

InfoPanelCellRenderer() - Constructor for class weka.gui.sql.InfoPanelCellRenderer

the constructor

InformationRetrievalEvaluationMetric - Interface in weka.classifiers.evaluation

An interface for information retrieval evaluation metrics to implement.

InformationTheoreticEvaluationMetric - Interface in weka.classifiers.evaluation

Primarily a marker interface for information theoretic evaluation metrics to implement.

Init(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Init defines a minimal Bayes net with no arcs

init(Environment) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Initialize this attribute spec by resolving any environment variables and setting up the date format (if necessary)

init() - Static method in class weka.gui.beans.BeanConnection

Sets up just a single collection of bean connections in the first element of the list.

init() - Static method in class weka.gui.beans.BeanInstance

Sets up just a single collection of bean instances in the first element of the list.

init(Environment, Instances) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Initialize this match rule by substituting any environment variables in the attributes, match and label strings.

init(Environment, Instances) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Initialize this match replace rule by substituting any environment variables in the attributes, match and replace strings.

initAsNaiveBayesTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

initComponent() - Method in class weka.gui.beans.InteractiveTablePanel

Initializes the component

initCPTs() - Method in class weka.classifiers.bayes.BayesNet

initializes the conditional probabilities

initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

initCPTs reserves space for CPTs and set all counts to zero

initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

initCPTs reserves space for CPTs and set all counts to zero

initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

initCPTs reserves space for CPTs and set all counts to zero

initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator

initCPTs reserves space for CPTs and set all counts to zero

initDefaultFilters() - Static method in class weka.gui.ConverterFileChooser

Initialize the default set of filters for loaders and savers

initFileClassIndexTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns the tip text for this property

initFileTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns the tip text for this property

initFilter(Instances) - Method in class weka.filters.unsupervised.attribute.KernelFilter

initializes the filter with the given dataset, i.e., the kernel gets built.

INITIAL_STEP - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

initialAnchorRandomTipText() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns the tip text for this property.

initialCountTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

initializationMethodTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property.

initialize() - Method in class weka.classifiers.CostMatrix

Initializes the matrix

initialize() - Method in class weka.classifiers.trees.j48.Distribution

Sets all counts to zero.

initialize(int, int, int) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Resets the object of split information

initialize(int, int, int) - Method in class weka.classifiers.trees.m5.YongSplitInfo

Resets the object of split information

initialize() - Static method in class weka.core.converters.ConverterUtils

initialize(File) - Method in class weka.experiment.DatabaseUtils

Initializes the database connection.

initialize(Properties) - Method in class weka.experiment.DatabaseUtils

Initializes the database connection.

initialize() - Method in class weka.experiment.Experiment

Prepares an experiment for running, initializing current iterator settings.

initialize() - Method in class weka.experiment.RemoteExperiment

Prepares a remote experiment for running, creates sub experiments

initialize() - Method in class weka.gui.visualize.BMPWriter

further initialization.

initialize() - Method in class weka.gui.visualize.JPEGWriter

further initialization.

initialize() - Method in class weka.gui.visualize.PNGWriter

further initialization.

initializeClassifier(Instances) - Method in interface weka.classifiers.IterativeClassifier

Initializes an iterative classifier.

initializeClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost

Builds the boosted classifier

initializeDistanceFunction(Instances) - Method in class weka.clusterers.Canopy

Initialize the distance function (i.e set min/max values for numeric attributes) with the supplied instances.

initializeDown(boolean) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

initializeRanges(int) - Method in class weka.core.Debug.DBO

Initialize ranges, upper limit must be set

initializeRanges() - Method in class weka.core.NormalizableDistance

Initializes the ranges using all instances of the dataset.

initializeRanges(int[]) - Method in class weka.core.NormalizableDistance

Initializes the ranges of a subset of the instances of this dataset.

initializeRanges(int[], int, int) - Method in class weka.core.NormalizableDistance

Initializes the ranges of a subset of the instances of this dataset.

initializeRangesEmpty(int, double[][]) - Method in class weka.core.NormalizableDistance

Used to initialize the ranges.

initializeStatistics() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Triggers construction of estimator based on current data and then initializes the statistics.

initializeUp() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

initInternalFields() - Method in class weka.gui.visualize.MatrixPanel

Initializes internal data fields, i.e.

initPMML() - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

Initializes a PMML object with header information.

initStructure() - Method in class weka.classifiers.bayes.BayesNet

Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).

InlineTable - Class in weka.core.pmml.jaxbbindings

Java class for InlineTable element declaration.

InlineTable() - Constructor for class weka.core.pmml.jaxbbindings.InlineTable

innerProduct(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Returns the inner product of two DoubleVectors

INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is an input unit.

input(Instance) - Method in class weka.filters.AllFilter

Input an instance for filtering.

input(Instance) - Method in class weka.filters.Filter

Input an instance for filtering.

input(Instance) - Method in class weka.filters.SimpleBatchFilter

Input an instance for filtering.

input(Instance) - Method in class weka.filters.SimpleStreamFilter

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.AttributeSelection

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.ClassOrder

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.Discretize

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.NominalToBinary

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.PartitionMembership

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.instance.Resample

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.instance.SpreadSubsample

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Add

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddCluster

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddExpression

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddID

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddNoise

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddUserFields

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.AddValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Center

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Copy

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Discretize

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.FirstOrder

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.MathExpression

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToString

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Normalize

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericToBinary

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Obfuscate

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Remove

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveType

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.Reorder

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

input(Instance) - Method in class weka.filters.unsupervised.attribute.Standardize

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToNominal

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.SwapValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.Randomize

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemovePercentage

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveRange

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.Resample

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.ReservoirSample

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Input an instance for filtering.

input(Instance) - Method in class weka.gui.streams.InstanceCounter

input(Instance) - Method in class weka.gui.streams.InstanceJoiner

input(Instance) - Method in class weka.gui.streams.InstanceSavePanel

input(Instance) - Method in class weka.gui.streams.InstanceTable

input(Instance) - Method in class weka.gui.streams.InstanceViewer

inputFormat(Instances) - Method in class weka.gui.streams.InstanceCounter

inputFormat(Instances) - Method in class weka.gui.streams.InstanceJoiner

Sets the format of the input instances.

inputFormat(Instances) - Method in class weka.gui.streams.InstanceSavePanel

inputFormat(Instances) - Method in class weka.gui.streams.InstanceTable

inputFormat(Instances) - Method in class weka.gui.streams.InstanceViewer

InputMappedClassifier - Class in weka.classifiers.misc

Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure.

InputMappedClassifier() - Constructor for class weka.classifiers.misc.InputMappedClassifier

InputMappedClassifierBeanInfo - Class in weka.classifiers.misc

Bean info class for the InputMappedClassifier.

InputMappedClassifierBeanInfo() - Constructor for class weka.classifiers.misc.InputMappedClassifierBeanInfo

inputOrderTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

inputs(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection

Returns a vector of BeanInstances that can be considered as inputs (or the left-hand side of a sub-flow)

inputsContains(BeanInstance) - Method in class weka.gui.beans.MetaBean

inRanges(Instance, double[][]) - Method in class weka.core.NormalizableDistance

Test if an instance is within the given ranges.

insert(int) - Method in class weka.classifiers.functions.supportVector.SMOset

Inserts an element into the set.

insert(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Inserts a new entry in the hashtable using the specified key.

insertAttributeAt(int) - Method in class weka.core.AbstractInstance

Inserts an attribute at the given position (0 to numAttributes()).

insertAttributeAt(int) - Method in interface weka.core.Instance

Inserts an attribute at the given position (0 to numAttributes()).

insertAttributeAt(Attribute, int) - Method in class weka.core.Instances

Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.

insertDummyNominalFirstValueTipText() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Returns the tip text for this property

insertElementAt(E, int) - Method in class weka.core.FastVector

Deprecated. Inserts an element at the given position.

insertElementAt(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Inserts the specified object as a component in this list at the specified index.

insertString(int, String, AttributeSet) - Method in class weka.gui.scripting.SyntaxDocument

Override to apply syntax highlighting after the document has been updated.

installedPackageResourceExists(String, String) - Static method in class weka.core.WekaPackageManager

Check if a named resource exists in an installed package

installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode

Traverses the tree and installs linear models at each node.

installNodeNums(int) - Method in class weka.classifiers.trees.ht.HNode

installNodeNums(int) - Method in class weka.classifiers.trees.ht.SplitNode

installPackageFromArchive(String, PrintStream...) - Static method in class weka.core.WekaPackageManager

Install a package from an archive

installPackageFromRepository(String, String, PrintStream...) - Static method in class weka.core.WekaPackageManager

Install a named package by retrieving the location of the archive from the meta data stored in the repository

installPackageFromURL(URL, PrintStream...) - Static method in class weka.core.WekaPackageManager

Insstall a package from the supplied URL

installPackages(List<Package>, PrintStream...) - Static method in class weka.core.WekaPackageManager

Install the supplied list of packages

installSmoothedModels() - Method in class weka.classifiers.trees.m5.RuleNode

Instance - Interface in weka.core

Interface representing an instance.

instance(int) - Method in class weka.core.Instances

Returns the instance at the given position.

INSTANCE_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent

INSTANCE_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent

Specifies that an instance is available

InstanceComparator - Class in weka.core

A comparator for the Instance class.

InstanceComparator() - Constructor for class weka.core.InstanceComparator

Initializes the comparator and includes the class in the comparison and all attributes included.

InstanceComparator(boolean) - Constructor for class weka.core.InstanceComparator

Initializes the comparator with all attributes included.

InstanceComparator(boolean, String, boolean) - Constructor for class weka.core.InstanceComparator

Initializes the comparator.

InstanceCounter - Class in weka.gui.streams

A bean that counts instances streamed to it.

InstanceCounter() - Constructor for class weka.gui.streams.InstanceCounter

InstanceEvent - Class in weka.gui.beans

Event that encapsulates a single instance or header information only

InstanceEvent(Object, Instance, int) - Constructor for class weka.gui.beans.InstanceEvent

Creates a new InstanceEvent instance that encapsulates a single instance only.

InstanceEvent(Object, Instances) - Constructor for class weka.gui.beans.InstanceEvent

Creates a new InstanceEvent instance which encapsulates header information only.

InstanceEvent(Object) - Constructor for class weka.gui.beans.InstanceEvent

InstanceEvent - Class in weka.gui.streams

An event encapsulating an instance stream event.

InstanceEvent(Object, int) - Constructor for class weka.gui.streams.InstanceEvent

Constructs an InstanceEvent with the specified source object and event type

InstanceField - Class in weka.core.pmml.jaxbbindings

Java class for InstanceField element declaration.

InstanceField() - Constructor for class weka.core.pmml.jaxbbindings.InstanceField

InstanceFields - Class in weka.core.pmml.jaxbbindings

Java class for InstanceFields element declaration.

InstanceFields() - Constructor for class weka.core.pmml.jaxbbindings.InstanceFields

InstanceInfo - Interface in weka.gui.visualize

Interface for JFrames that display instance info.

InstanceInfoFrame - Class in weka.gui.visualize

Frame for displaying information on the displayed data.

InstanceInfoFrame() - Constructor for class weka.gui.visualize.InstanceInfoFrame

Initializes the frame.

InstanceJoiner - Class in weka.gui.streams

A bean that joins two streams of instances into one.

InstanceJoiner() - Constructor for class weka.gui.streams.InstanceJoiner

Setup the initial states of the member variables

InstanceListener - Interface in weka.gui.beans

Interface to something that can accept instance events

InstanceListener - Interface in weka.gui.streams

An interface for objects interested in listening to streams of instances.

InstanceLoader - Class in weka.gui.streams

A bean that produces a stream of instances from a file.

InstanceLoader() - Constructor for class weka.gui.streams.InstanceLoader

instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceCounter

instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner

instanceProduced(InstanceEvent) - Method in interface weka.gui.streams.InstanceListener

instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceSavePanel

instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceTable

instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceViewer

InstanceProducer - Interface in weka.gui.streams

An interface for objects capable of producing streams of instances.

InstanceQuery - Class in weka.experiment

Convert the results of a database query into instances.

InstanceQuery() - Constructor for class weka.experiment.InstanceQuery

Sets up the database drivers

InstanceQueryAdapter - Interface in weka.experiment

An interface implemented by InstanceQuery and any user class that is to be passed as the first argument to InstanceQuery.retrieveInstances(InstanceQueryAdapter, ResultSet).

instanceRangeTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Returns the tip text for this property

Instances - Class in weka.core

Class for handling an ordered set of weighted instances.

Instances(Reader) - Constructor for class weka.core.Instances

Reads an ARFF file from a reader, and assigns a weight of one to each instance.

Instances(Reader, int) - Constructor for class weka.core.Instances

Deprecated. instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.

Instances(Instances) - Constructor for class weka.core.Instances

Constructor copying all instances and references to the header information from the given set of instances.

Instances(Instances, int) - Constructor for class weka.core.Instances

Constructor creating an empty set of instances.

Instances(Instances, int, int) - Constructor for class weka.core.Instances

Creates a new set of instances by copying a subset of another set.

Instances(String, ArrayList<Attribute>, int) - Constructor for class weka.core.Instances

Creates an empty set of instances.

InstanceSavePanel - Class in weka.gui.streams

A bean that saves a stream of instances to a file.

InstanceSavePanel() - Constructor for class weka.gui.streams.InstanceSavePanel

instancesIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns the tip text for this property

InstancesResultListener - Class in weka.experiment

Outputs the received results in arff format to a Writer.

InstancesResultListener() - Constructor for class weka.experiment.InstancesResultListener

Sets temporary file.

InstancesSummaryPanel - Class in weka.gui

This panel just displays relation name, number of instances, and number of attributes.

InstancesSummaryPanel() - Constructor for class weka.gui.InstancesSummaryPanel

Creates the instances panel with no initial instances.

InstanceStreamToBatchMaker - Class in weka.gui.beans

Bean that converts an instance stream into a (batch) data set.

InstanceStreamToBatchMaker() - Constructor for class weka.gui.beans.InstanceStreamToBatchMaker

InstanceStreamToBatchMakerBeanInfo - Class in weka.gui.beans

BeanInfo class for the InstanceStreamToBatchMaker bean

InstanceStreamToBatchMakerBeanInfo() - Constructor for class weka.gui.beans.InstanceStreamToBatchMakerBeanInfo

InstanceTable - Class in weka.gui.streams

A bean that takes a stream of instances and displays in a table.

InstanceTable() - Constructor for class weka.gui.streams.InstanceTable

instanceToSchema(Instance, MiningSchema) - Method in class weka.core.pmml.MappingInfo

Convert an Instance to an array of values that matches the format of the mining schema.

InstanceViewer - Class in weka.gui.streams

This is a very simple instance viewer - just displays the dataset as text output as it would be written to a file.

InstanceViewer() - Constructor for class weka.gui.streams.InstanceViewer

intCount - Variable in class weka.core.AttributeStats

The number of int-like values

INTEGER - Static variable in interface weka.core.json.sym

INTEGER - Static variable in class weka.datagenerators.clusterers.SubspaceCluster

cluster subtype: integer

INTEGER - Static variable in class weka.experiment.DatabaseUtils

Type mapping for INTEGER used for reading experiment results.

InteractiveTableModel - Class in weka.gui.beans

Table model that automatically adds a new row to the table on pressing enter in the last cell of a row.

InteractiveTableModel(String[]) - Constructor for class weka.gui.beans.InteractiveTableModel

Constructor

InteractiveTablePanel - Class in weka.gui.beans

Provides a panel using an interactive table model.

InteractiveTablePanel(String[]) - Constructor for class weka.gui.beans.InteractiveTablePanel

Constructor

InteractiveTablePanel.InteractiveTableModelListener - Class in weka.gui.beans

Listener for the InteractiveTablePanel

InteractiveTablePanel.InteractiveTableModelListener() - Constructor for class weka.gui.beans.InteractiveTablePanel.InteractiveTableModelListener

intercept() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel

Return the intercept

internalCacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the tip text for this property

INTERPOLATIONMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for INTERPOLATION-METHOD.

InterquartileRange - Class in weka.filters.unsupervised.attribute

A filter for detecting outliers and extreme values based on interquartile ranges.

InterquartileRange() - Constructor for class weka.filters.unsupervised.attribute.InterquartileRange

InterquartileRange.ValueType - Enum in weka.filters.unsupervised.attribute

enum for obtaining the various determined IQR values.

Interval - Class in weka.core.pmml.jaxbbindings

Java class for Interval element declaration.

Interval() - Constructor for class weka.core.pmml.jaxbbindings.Interval

IntervalBasedEvaluationMetric - Interface in weka.classifiers.evaluation

Primarily a marker interface for interval-based evaluation metrics to implement.

IntervalEstimator - Interface in weka.classifiers

Interface for numeric prediction schemes that can output prediction intervals.

INTSparseArray - Class in weka.core.pmml.jaxbbindings

Java class for INT-SparseArray element declaration.

INTSparseArray() - Constructor for class weka.core.pmml.jaxbbindings.INTSparseArray

IntVector - Class in weka.core.matrix

A vector specialized on integers.

IntVector() - Constructor for class weka.core.matrix.IntVector

Constructs a null vector.

IntVector(int) - Constructor for class weka.core.matrix.IntVector

Constructs an n-vector of zeros.

IntVector(int, int) - Constructor for class weka.core.matrix.IntVector

Constructs an n-vector of a constant

IntVector(int[]) - Constructor for class weka.core.matrix.IntVector

Constructs a vector given an int array

INVALIDVALUETREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for INVALID-VALUE-TREATMENT-METHOD.

INVERSE - Static variable in class weka.classifiers.lazy.LWL

inverse() - Method in class weka.core.matrix.Matrix

Matrix inverse or pseudoinverse

invertSelectionTipText() - Method in class weka.core.NormalizableDistance

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.supervised.attribute.Discretize

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.supervised.instance.Resample

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Copy

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Discretize

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Remove

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.Resample

Returns the tip text for this property

invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the tip text for this property

invoke(String, Class<?>[], Object[]) - Method in class weka.core.scripting.Groovy

executes the specified method on the current interpreter and returns the result, if any.

invoke(Object, String, Class<?>[], Object[]) - Static method in class weka.core.scripting.Groovy

executes the specified method and returns the result, if any.

invoke(String, Class<?>[], Object[]) - Method in class weka.core.scripting.Jython

executes the specified method on the current interpreter and returns the result, if any.

invoke(Object, String, Class<?>[], Object[]) - Static method in class weka.core.scripting.Jython

executes the specified method and returns the result, if any

invokeMain(String, String[]) - Static method in class weka.gui.SplashWindow

Invokes the main method of the provided class name.

invokeMethod(String, String, String[]) - Static method in class weka.gui.SplashWindow

Invokes the named method of the provided class name.

IRClassValueTipText() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns the tip text for this property

is(String) - Method in class weka.core.Stopwords

Returns true if the given string is a stop word.

IS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

isALeaf() - Method in class weka.core.neighboursearch.balltrees.BallNode

Returns true if the node is a leaf node (if both its left and right child are null).

isALeaf() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode

Returns whether if the node is a leaf or not.

isALeaf() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode

Checks if node is a leaf.

isAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler

returns whether the given property (display name) is allowed for the given class.

isAllowed(Object, String) - Method in class weka.core.xml.PropertyHandler

returns whether the given property (display name) is allowed for the given object .

isAnonymous() - Method in class weka.core.json.JSONNode

Checks whether the node is anonymous.

isArff(String) - Static method in class weka.core.converters.ConverterUtils.DataSource

returns whether the extension of the location is likely to be of ARFF format, i.e., ending in ".arff" or ".arff.gz" (case-insensitive).

isArray() - Method in class weka.core.json.JSONNode

Returns wether the node is an array.

isArray(Element) - Static method in class weka.core.pmml.Array

Utility method to check if an XML element is an array.

isAttribute() - Method in enum weka.core.Capabilities.Capability

returns true if the capability is an attribute

isAttributeCapability() - Method in enum weka.core.Capabilities.Capability

returns true if the capability is an attribute capability

isAveragable() - Method in class weka.core.Attribute

Returns whether the attribute can be averaged meaningfully.

isBoolean(int) - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns true if attribute is boolean

isBorderOpaque() - Method in class weka.gui.beans.ShadowBorder

This implementation always returns true.

isBusy() - Method in class weka.gui.beans.Appender

Returns true if.

isBusy() - Method in class weka.gui.beans.Associator

Returns true if.

isBusy() - Method in interface weka.gui.beans.BeanCommon

Returns true if.

isBusy() - Method in class weka.gui.beans.ClassAssigner

Returns true if.

isBusy() - Method in class weka.gui.beans.Classifier

Returns true if.

isBusy() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Returns true if.

isBusy() - Method in class weka.gui.beans.ClassValuePicker

Returns true if.

isBusy() - Method in class weka.gui.beans.Clusterer

Returns true if.

isBusy() - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Returns true if.

isBusy() - Method in class weka.gui.beans.CostBenefitAnalysis

Returns true if.

isBusy() - Method in class weka.gui.beans.CrossValidationFoldMaker

Returns true if.

isBusy() - Method in class weka.gui.beans.DataVisualizer

Returns true if.

isBusy() - Method in class weka.gui.beans.Filter

Returns true if.

isBusy() - Method in class weka.gui.beans.FlowByExpression

isBusy() - Method in class weka.gui.beans.ImageSaver

isBusy() - Method in class weka.gui.beans.ImageViewer

isBusy() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Returns true if.

isBusy() - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Returns true if.

isBusy() - Method in class weka.gui.beans.Join

Returns true if we are doing something

isBusy() - Method in class weka.gui.beans.Loader

Returns true if.

isBusy() - Method in class weka.gui.beans.MetaBean

Returns true if.

isBusy() - Method in class weka.gui.beans.ModelPerformanceChart

Returns true if.

isBusy() - Method in class weka.gui.beans.PredictionAppender

Returns true if.

isBusy() - Method in class weka.gui.beans.Saver

Returns true if.

isBusy() - Method in class weka.gui.beans.SerializedModelSaver

Returns true if.

isBusy() - Method in class weka.gui.beans.Sorter

Returns true if.

isBusy() - Method in class weka.gui.beans.StripChart

Returns true if.

isBusy() - Method in class weka.gui.beans.SubstringLabeler

Returns true if.

isBusy() - Method in class weka.gui.beans.SubstringReplacer

Returns true if.

isBusy() - Method in class weka.gui.beans.TestSetMaker

Returns true if.

isBusy() - Method in class weka.gui.beans.TextSaver

isBusy() - Method in class weka.gui.beans.TextViewer

Returns true if.

isBusy() - Method in class weka.gui.beans.TrainingSetMaker

Returns true if.

isBusy() - Method in class weka.gui.beans.TrainTestSplitMaker

Returns true if.

isCellEditable(int, int) - Method in class weka.gui.arffviewer.ArffTableModel

returns true if the cell at rowindex and columnindexis editable

isCellEditable(int, int) - Method in class weka.gui.beans.InteractiveTableModel

isCellEditable(int, int) - Method in class weka.gui.SortedTableModel

Returns true if the cell at rowIndex and columnIndex is editable.

isCellEditable(int, int) - Method in class weka.gui.sql.ResultSetTableModel

returns true if the cell at rowindex and columnindexis editable.

isChanged() - Method in class weka.classifiers.bayes.net.EditableBayesNet

return true when current state differs from the state the network was last saved

isChanged() - Method in class weka.gui.arffviewer.ArffPanel

returns whether the content of the panel was changed

isChanged() - Method in class weka.gui.ViewerDialog

returns whether the data has been changed

isClass() - Method in enum weka.core.Capabilities.Capability

returns true if the capability is a class

isClassCapability() - Method in enum weka.core.Capabilities.Capability

returns true if the capability is a other capability

isClassname(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

tests whether the given partial string is the name of a class with classpath - it basically tests, whether the string consists only of alphanumeric literals, underscores and dots.

isConnected() - Method in class weka.experiment.DatabaseUtils

Returns true if a database connection is active.

isConnected() - Method in class weka.gui.sql.event.ConnectionEvent

returns whether the connection is still open.

isContinuous() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

checks, whether cluster sub type is continuous

isCoreFileLoader(String) - Static method in class weka.core.converters.ConverterUtils

checks whether the given class is one of the hardcoded core file loaders.

isCoreFileSaver(String) - Static method in class weka.core.converters.ConverterUtils

checks whether the given class is one of the hardcoded core file savers.

isCpuTime() - Method in class weka.core.Debug.Clock

whether the measurement is based on the msecs returned from the System class or on the more accurate CPU time.

isCursorScrollable() - Method in class weka.experiment.DatabaseUtils

Checks whether cursors are scrollable in general, false otherwise (also if not connected).

isCursorScrollSensitive() - Method in class weka.experiment.DatabaseUtils

Returns whether the cursors only support forward movement or are scroll sensitive (with ResultSet.CONCUR_READ_ONLY concurrency).

isDate() - Method in class weka.core.Attribute

Tests if the attribute is a date type.

isDelimiter(String) - Method in class weka.gui.scripting.SyntaxDocument

Checks whether the character is a delimiter.

isEmpty() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Tests if this hashtable maps no keys to values.

isEmpty() - Method in class weka.core.matrix.DoubleVector

Checks if it is an empty vector

isEmpty() - Method in class weka.core.matrix.IntVector

Returns true if the vector is empty

isEmpty() - Method in class weka.core.Trie

Returns true if this collection contains no elements.

isEnabled(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities

whether the given capability is enabled.

isEnabled() - Method in class weka.core.Memory

returns whether the memory management is enabled

isEnabledNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities

whether the given "not to have" capability is enabled.

isFirstBatchDone() - Method in class weka.filters.Filter

Returns true if the first batch of instances got processed.

isFullRank() - Method in class weka.core.matrix.QRDecomposition

Is the matrix full rank?

isGaussian() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

checks, whether cluster type is gaussian

isHidden() - Method in class weka.gui.beans.BeanConnection

Returns true if this connection is invisible

isHierachic(String) - Method in class weka.gui.HierarchyPropertyParser

Whether the given string has a hierachy structure with the seperators

isIgnored(String) - Method in class weka.core.xml.PropertyHandler

checks whether the given display name is an ignored property

isIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler

checks whether the given display name of a certain class is an ignored property.

isIgnored(Object, String) - Method in class weka.core.xml.PropertyHandler

checks whether the given display name of a given object is an ignored property.

isIncremental() - Method in class weka.core.converters.ConverterUtils.DataSource

returns whether the loader is an incremental one.

isInDisabledList(String) - Static method in class weka.gui.beans.PluginManager

Returns true if the supplied fully qualified class name is in the disabled list

isInitialAnchorRandom() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Gets whether if the initial anchor is chosen randomly.

isInRange(double) - Method in class weka.core.Attribute

Determines whether a value lies within the bounds of the attribute.

isInRange(int) - Method in class weka.core.Range

Gets whether the supplied cardinal number is included in the current range.

isInteger() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

checks, whether cluster sub type is integer

isIsIntercept() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Gets the value of the isIntercept property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.MiningModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TextModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Gets the value of the isScorable property.

isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TreeModel

Gets the value of the isScorable property.

isIsTransformed() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Gets the value of the isTransformed property.

isKeyword(String) - Method in class weka.experiment.DatabaseUtils

Checks whether the given string is a reserved keyword.

isKOML(String) - Static method in class weka.core.xml.SerialUIDChanger

checks whether the given filename ends with ".koml"

isLeaf() - Method in class weka.classifiers.trees.ht.HNode

Returns true if this is a leaf

isLeaf() - Method in class weka.classifiers.trees.ht.SplitNode

isLeaf() - Method in class weka.classifiers.trees.m5.RuleNode

Return true if this node is a leaf

isLeafReached() - Method in class weka.gui.HierarchyPropertyParser

Whether the current position is a leaf

isMissing(int) - Method in class weka.core.AbstractInstance

Tests if a specific value is "missing".

isMissing(Attribute) - Method in class weka.core.AbstractInstance

Tests if a specific value is "missing".

isMissing(int) - Method in interface weka.core.Instance

Tests if a specific value is "missing".

isMissing(Attribute) - Method in interface weka.core.Instance

Tests if a specific value is "missing".

ISMISSING - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

checks whether the value at the given position is missing

isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel

checks whether the value at the given position is missing

isMissingSparse(int) - Method in class weka.core.AbstractInstance

Tests if a specific value is "missing", given an index in the sparse representation.

isMissingSparse(int) - Method in interface weka.core.Instance

Tests if a specific value is "missing" in the sparse representation.

isMissingValue(double) - Static method in class weka.core.Utils

Tests if the given value codes "missing".

isModified() - Method in class weka.gui.scripting.Script

Returns whether the script is modified.

isMonitoring() - Method in class weka.gui.MemoryUsagePanel

Returns whether the thread is still running.

isNewBatch() - Method in class weka.filters.Filter

Returns true if the a new batch was started, either a new instance of the filter was created or the batchFinished() method got called.

isNewer(String) - Method in class weka.core.Version

checks whether this version is newer than the one from the given version string

isNominal() - Method in class weka.core.Attribute

Test if the attribute is nominal.

isNominal(int) - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns true if attribute is nominal

isNominal() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns true if selection attribute is nominal.

isNominal() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns true if selection attribute is nominal.

isNonsingular() - Method in class weka.core.matrix.LUDecomposition

Is the matrix nonsingular?

isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns whether the notification of changes is enabled

isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffTableModel

returns whether the notification of changes is enabled

isNullAt(int, int) - Method in class weka.gui.sql.ResultSetTableModel

checks whether the value of the cell is NULL.

isNumeric() - Method in class weka.core.Attribute

Tests if the attribute is numeric.

isNumeric() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns true if selection attribute is numeric.

isNumericAt(int) - Method in class weka.gui.sql.ResultSetTableModel

returns whether the column at the given index is numeric.

isObject() - Method in class weka.core.json.JSONNode

Returns wether the node is an object.

isOlder(String) - Method in class weka.core.Version

checks whether this version is older than the one from the given version string

isOtherCapability() - Method in enum weka.core.Capabilities.Capability

returns true if the capability is a class capability

isOutOfMemory() - Method in class weka.core.Memory

checks if there's still enough memory left by checking whether there is still a 50MB margin between getUsed() and getMax().

isOutputFormatDefined() - Method in class weka.filters.Filter

Returns whether the output format is ready to be collected

isOutputFormatDefined() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns whether the output format is ready to be collected

isPaintable() - Method in class weka.gui.beans.EnvironmentField

isPaintable() - Method in class weka.gui.CostMatrixEditor

Indicates whether the object can be represented graphically.

isPaintable() - Method in class weka.gui.FileEditor

Returns true since this editor is paintable.

isPaintable() - Method in class weka.gui.GenericArrayEditor

Returns true to indicate that we can paint a representation of the string array.

isPaintable() - Method in class weka.gui.GenericObjectEditor

Returns true to indicate that we can paint a representation of the Object.

isPaintable() - Method in class weka.gui.SimpleDateFormatEditor

Indicates whether the object can be represented graphically.

isPanelSelected() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

checks whether a panel is currently selected

isPresent() - Static method in class weka.core.scripting.Groovy

returns whether the Groovy classes are present or not, i.e.

isPresent() - Static method in class weka.core.scripting.Jython

returns whether the Jython classes are present or not, i.e.

isPresent() - Static method in class weka.core.stemmers.SnowballStemmer

returns whether Snowball is present or not, i.e.

isPresent() - Static method in class weka.core.xml.KOML

returns whether KOML is present or not, i.e.

isPresent() - Static method in class weka.core.xml.XStream

returns whether XStream is present or not, i.e.

isPrimitive() - Method in class weka.core.json.JSONNode

Returns whether the node stores a primitive value or a an array/object.

isQuoteDelimiter(String) - Method in class weka.gui.scripting.SyntaxDocument

Checks whether the character is quote delimiter.

isRandom() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

checks, whether cluster type is random

isReadOnly() - Method in class weka.gui.arffviewer.ArffPanel

returns whether the model is read-only

isReadOnly() - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns whether the model is read-only

isReadOnly() - Method in class weka.gui.arffviewer.ArffTable

returns whether the model is read-only

isReadOnly() - Method in class weka.gui.arffviewer.ArffTableModel

returns whether the model is read-only

isRegular() - Method in class weka.core.Attribute

Returns whether the attribute values are equally spaced.

isRelationValued() - Method in class weka.core.Attribute

Tests if the attribute is relation valued.

isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.AveragingResultProducer

Determines whether the results for a specified key must be generated.

isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.CSVResultListener

Always says a result is required.

isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultListener

Always says a result is required.

isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultProducer

Determines whether the results for a specified key must be generated.

isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.LearningRateResultProducer

Determines whether the results for a specified key must be generated.

isResultRequired(ResultProducer, Object[]) - Method in interface weka.experiment.ResultListener

Determines whether the results for a specified key must be generated.

isRootReached() - Method in class weka.gui.HierarchyPropertyParser

Whether the current position is the root

isRunning() - Method in class weka.core.Debug.Clock

whether the time is still being clocked

isRunning() - Method in class weka.gui.scripting.Script

Returns whether the script is still running.

isSaved() - Method in class weka.classifiers.bayes.net.EditableBayesNet

indicate the network state was saved

isSerializable(String) - Static method in class weka.core.SerializationHelper

checks whether a class is serializable.

isSerializable(Class<?>) - Static method in class weka.core.SerializationHelper

checks whether a class is serializable.

isSorted() - Method in class weka.gui.SortedTableModel

returns whether the table was sorted

isSparse() - Method in class weka.core.pmml.Array

Is this array a SparseArray?

isSparse() - Method in class weka.core.pmml.SparseArray

Overrides isSparse() in Array and always returns true.

isSPD() - Method in class weka.core.matrix.CholeskyDecomposition

Is the matrix symmetric and positive definite?

isSquare() - Method in class weka.core.matrix.Matrix

returns whether the matrix is a square matrix or not.

isStopword(String) - Static method in class weka.core.Stopwords

Returns true if the given string is a stop word.

isStreamableFilter() - Method in class weka.filters.MultiFilter

tests whether all the enclosed filters are streamable

isString() - Method in class weka.core.Attribute

Tests if the attribute is a string.

isStructureOnly() - Method in class weka.gui.beans.DataSetEvent

Returns true if the encapsulated instances contain just header information

isStructureOnly() - Method in class weka.gui.beans.TestSetEvent

Returns true if the encapsulated instances contain just header information

isStructureOnly() - Method in class weka.gui.beans.TrainingSetEvent

Returns true if the encapsulated instances contain just header information

isSubclass(String, String) - Static method in class weka.core.ClassDiscovery

Checks whether the "otherclass" is a subclass of the given "superclass".

isSubclass(Class<?>, Class<?>) - Static method in class weka.core.ClassDiscovery

Checks whether the "otherclass" is a subclass of the given "superclass".

isSymmetric() - Method in class weka.core.Matrix

Deprecated. Returns true if the matrix is symmetric.

isSymmetric() - Method in class weka.core.matrix.Matrix

Returns true if the matrix is symmetric.

isUndoEnabled() - Method in interface weka.core.Undoable

returns whether undo support is enabled

isUndoEnabled() - Method in class weka.gui.arffviewer.ArffPanel

returns whether undo support is enabled

isUndoEnabled() - Method in class weka.gui.arffviewer.ArffSortedTableModel

returns whether undo support is enabled

isUndoEnabled() - Method in class weka.gui.arffviewer.ArffTableModel

returns whether undo support is enabled

isUniform() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

checks, whether cluster type is uniform

isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Returns whether K2 prior is used

isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

isUseReasonCodes() - Method in class weka.core.pmml.jaxbbindings.Scorecard

Gets the value of the useReasonCodes property.

isUseVariant1() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Whether variant 1 is used

Item - Class in weka.associations

Class that encapsulates information about an individual item.

Item(Attribute) - Constructor for class weka.associations.Item

Item - Class in weka.core.pmml.jaxbbindings

Java class for Item element declaration.

Item() - Constructor for class weka.core.pmml.jaxbbindings.Item

itemAt(int) - Method in class weka.associations.ItemSet

Gest the index of the value of the specified attribute

ItemRef - Class in weka.core.pmml.jaxbbindings

Java class for ItemRef element declaration.

ItemRef() - Constructor for class weka.core.pmml.jaxbbindings.ItemRef

items() - Method in class weka.associations.ItemSet

Gest the item set as an int array

ItemSet - Class in weka.associations

Class for storing a set of items.

ItemSet(int) - Constructor for class weka.associations.ItemSet

Constructor

ItemSet(int, int[]) - Constructor for class weka.associations.ItemSet

Constructor

ItemSet(int[]) - Constructor for class weka.associations.ItemSet

Contsructor

Itemset - Class in weka.core.pmml.jaxbbindings

Java class for Itemset element declaration.

Itemset() - Constructor for class weka.core.pmml.jaxbbindings.Itemset

itemStateChanged(ItemEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Performs the action associated with the ItemEvent.

IteratedLovinsStemmer - Class in weka.core.stemmers

An iterated version of the Lovins stemmer.

IteratedLovinsStemmer() - Constructor for class weka.core.stemmers.IteratedLovinsStemmer

IteratedSingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.

IteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.IteratedSingleClassifierEnhancer

IterativeClassifier - Interface in weka.classifiers

Interface for classifiers that can induce models of growing complexity one step at a time.

IterativeClassifierOptimizer - Class in weka.classifiers.meta

Chooses the best number of iterations for an IterativeClassifier such as LogitBoost using cross-validation.

IterativeClassifierOptimizer() - Constructor for class weka.classifiers.meta.IterativeClassifierOptimizer

iterativeClassifierTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns the tip text for this property

iterator() - Method in class weka.core.Trie

Returns an iterator over the elements in this collection.

J

J48 - Class in weka.classifiers.trees

Class for generating a pruned or unpruned C4.5 decision tree.

J48() - Constructor for class weka.classifiers.trees.J48

Jaccard - Class in weka.core.pmml.jaxbbindings

Java class for jaccard element declaration.

Jaccard() - Constructor for class weka.core.pmml.jaxbbindings.Jaccard

Javadoc - Class in weka.core

Abstract superclass for classes that generate Javadoc comments and replace the content between certain comment tags.

Javadoc() - Constructor for class weka.core.Javadoc

JComponentWriter - Class in weka.gui.visualize

This class takes any JComponent and outputs it to a file.

JComponentWriter() - Constructor for class weka.gui.visualize.JComponentWriter

initializes the object

JComponentWriter(JComponent) - Constructor for class weka.gui.visualize.JComponentWriter

initializes the object with the given Component

JComponentWriter(JComponent, File) - Constructor for class weka.gui.visualize.JComponentWriter

initializes the object with the given Component and filename

JListHelper - Class in weka.gui

A helper class for JList GUI elements with DefaultListModel or derived models.

JListHelper() - Constructor for class weka.gui.JListHelper

Join - Class in weka.gui.beans

Join() - Constructor for class weka.gui.beans.Join

Constructor

JoinBeanInfo - Class in weka.gui.beans

BeanInfo for the Join step

JoinBeanInfo() - Constructor for class weka.gui.beans.JoinBeanInfo

JoinCustomizer - Class in weka.gui.beans

Customizer component for the Join step

JoinCustomizer() - Constructor for class weka.gui.beans.JoinCustomizer

joinOptions(String[]) - Static method in class weka.core.Utils

Joins all the options in an option array into a single string, as might be used on the command line.

JPEGWriter - Class in weka.gui.visualize

This class takes any JComponent and outputs it to a JPEG-file.

JPEGWriter() - Constructor for class weka.gui.visualize.JPEGWriter

initializes the object.

JPEGWriter(JComponent) - Constructor for class weka.gui.visualize.JPEGWriter

initializes the object with the given Component.

JPEGWriter(JComponent, File) - Constructor for class weka.gui.visualize.JPEGWriter

initializes the object with the given Component and filename.

JRip - Class in weka.classifiers.rules

This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.

JRip() - Constructor for class weka.classifiers.rules.JRip

JRip.Antd - Class in weka.classifiers.rules

The single antecedent in the rule, which is composed of an attribute and the corresponding value.

JRip.Antd(Attribute) - Constructor for class weka.classifiers.rules.JRip.Antd

Constructor

JRip.NominalAntd - Class in weka.classifiers.rules

The antecedent with nominal attribute

JRip.NominalAntd(Attribute) - Constructor for class weka.classifiers.rules.JRip.NominalAntd

Constructor

JRip.NumericAntd - Class in weka.classifiers.rules

The antecedent with numeric attribute

JRip.NumericAntd(Attribute) - Constructor for class weka.classifiers.rules.JRip.NumericAntd

Constructor

JRip.RipperRule - Class in weka.classifiers.rules

This class implements a single rule that predicts specified class.

JRip.RipperRule() - Constructor for class weka.classifiers.rules.JRip.RipperRule

Constructor

JSONInstances - Class in weka.core.json

Class for transforming Instances objects into JSON objects and vice versa.

JSONInstances() - Constructor for class weka.core.json.JSONInstances

JSONLoader - Class in weka.core.converters

Reads a source that is in the JSON format.
It automatically decompresses the data if the extension is '.json.gz'.

For more information, see JSON homepage:
http://www.json.org/

JSONLoader() - Constructor for class weka.core.converters.JSONLoader

JSONNode - Class in weka.core.json

Container class for storing a JSON data structure.

JSONNode() - Constructor for class weka.core.json.JSONNode

Initializes the root container.

JSONNode(String, Boolean) - Constructor for class weka.core.json.JSONNode

Initializes the primitive container.

JSONNode(String, Integer) - Constructor for class weka.core.json.JSONNode

Initializes the primitive container.

JSONNode(String, Double) - Constructor for class weka.core.json.JSONNode

Initializes the primitive container.

JSONNode(String, String) - Constructor for class weka.core.json.JSONNode

Initializes the primitive container.

JSONNode.NodeType - Enum in weka.core.json

The type of a node.

JSONSaver - Class in weka.core.converters

Writes to a destination that is in JSON format.
The data can be compressed with gzip, in order to save space.

For more information, see JSON homepage:
http://www.json.org/

Valid options are:

JSONSaver() - Constructor for class weka.core.converters.JSONSaver

Constructor.

JTableHelper - Class in weka.gui

A helper class for JTable, e.g.

JTableHelper(JTable) - Constructor for class weka.gui.JTableHelper

initializes the object

Jython - Class in weka.core.scripting

A helper class for Jython.

Jython() - Constructor for class weka.core.scripting.Jython

default constructor, tries to instantiate a Python Interpreter

JythonObject - Interface in weka.core.scripting

An indicator interface for Jython objects.

JythonPanel - Class in weka.gui.scripting

A scripting panel for Jython.

JythonPanel() - Constructor for class weka.gui.scripting.JythonPanel

JythonScript - Class in weka.gui.scripting

Represents a Jython script.

JythonScript() - Constructor for class weka.gui.scripting.JythonScript

Initializes the script.

JythonScript(Document) - Constructor for class weka.gui.scripting.JythonScript

Initializes the script.

JythonScript(Document, File) - Constructor for class weka.gui.scripting.JythonScript

Initializes the script.

JythonScript.JythonThread - Class in weka.gui.scripting

Executes a Jython script in a thread.

JythonScript.JythonThread(Script, String[]) - Constructor for class weka.gui.scripting.JythonScript.JythonThread

Initializes the thread.

JythonSerializableObject - Interface in weka.core.scripting

An indicator interface for serializable Jython objects.

K

K2 - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.

For more information see:

G.F.
K2() - Constructor for class weka.classifiers.bayes.net.search.global.K2
K2 - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.

For more information see:

G.F.
K2() - Constructor for class weka.classifiers.bayes.net.search.local.K2
kappa() - Method in class weka.classifiers.evaluation.Evaluation: Returns value of kappa statistic if class is nominal.
kappa() - Method in class weka.classifiers.Evaluation: Returns value of kappa statistic if class is nominal.
KBInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the total Kononenko & Bratko Information score in bits.
KBInformation() - Method in class weka.classifiers.Evaluation: Return the total Kononenko & Bratko Information score in bits.
KBMeanInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the Kononenko & Bratko Information score in bits per instance.
KBMeanInformation() - Method in class weka.classifiers.Evaluation: Return the Kononenko & Bratko Information score in bits per instance.
KBRelativeInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the Kononenko & Bratko Relative Information score.
KBRelativeInformation() - Method in class weka.classifiers.Evaluation: Return the Kononenko & Bratko Relative Information score.
KDConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
KDConditionalEstimator(int, double) - Constructor for class weka.estimators.KDConditionalEstimator: Constructor
KDDataGenerator - Class in weka.gui.boundaryvisualizer: KDDataGenerator.
KDDataGenerator() - Constructor for class weka.gui.boundaryvisualizer.KDDataGenerator
KDTree - Class in weka.core.neighboursearch: Class implementing the KDTree search algorithm for nearest neighbour search.
The connection to dataset is only a reference.
KDTree() - Constructor for class weka.core.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTree(Instances) - Constructor for class weka.core.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTreeNode - Class in weka.core.neighboursearch.kdtrees: A class representing a KDTree node.
KDTreeNode() - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][]) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][], double[][]) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode
KDTreeNodeSplitter - Class in weka.core.neighboursearch.kdtrees: Class that splits up a KDTreeNode.
KDTreeNodeSplitter() - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: default constructor.
KDTreeNodeSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Creates a new instance of KDTreeNodeSplitter.
Kernel - Class in weka.classifiers.functions.supportVector: Abstract kernel.
Kernel() - Constructor for class weka.classifiers.functions.supportVector.Kernel
KernelEstimator - Class in weka.estimators: Simple kernel density estimator.
KernelEstimator(double) - Constructor for class weka.estimators.KernelEstimator: Constructor that takes a precision argument.
KernelEvaluation - Class in weka.classifiers.functions.supportVector: Class for evaluating Kernels.
KernelEvaluation() - Constructor for class weka.classifiers.functions.supportVector.KernelEvaluation: default constructor
kernelFactorExpressionTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
KernelFilter - Class in weka.filters.unsupervised.attribute: Converts the given set of predictor variables into a kernel matrix.
KernelFilter() - Constructor for class weka.filters.unsupervised.attribute.KernelFilter
kernelMatrixFileTipText() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.GaussianProcesses: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
kernelTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
key - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: attribute value
keyFieldNameTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
keys() - Method in class weka.core.xml.MethodHandler: returns an enumeration over all currently stored custom methods, i.e.
keysTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
kFoldCV(BayesNet, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: kFoldCV uses k-fold cross validation to measure the accuracy of a Bayes network classifier.
KFStep - Annotation Type in weka.gui.beans: Optional annotation for plugin beans in the Knowledge Flow.
KKConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a numeric domain.
KKConditionalEstimator(double) - Constructor for class weka.estimators.KKConditionalEstimator: Constructor
KMEANS_PLUS_PLUS - Static variable in class weka.clusterers.SimpleKMeans
KMeansInpiredMethod - Class in weka.core.neighboursearch.kdtrees: The class that splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.

For more information see also:

Ashraf Masood Kibriya (2007).
KMeansInpiredMethod() - Constructor for class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.BallTree: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.CoverTree: Returns k-NNs of a given target instance, from among the previously supplied training instances (supplied through setInstances method) P.S.: May return more than k-NNs if more one instances have the same distance to the target as the kth NN.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.KDTree: Returns the k nearest neighbours of the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.LinearNNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
KNNInput - Class in weka.core.pmml.jaxbbindings: Java class for KNNInput element declaration.
KNNInput() - Constructor for class weka.core.pmml.jaxbbindings.KNNInput
KNNInputs - Class in weka.core.pmml.jaxbbindings: Java class for KNNInputs element declaration.
KNNInputs() - Constructor for class weka.core.pmml.jaxbbindings.KNNInputs
KNNTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
KNNTipText() - Method in class weka.classifiers.lazy.LWL: Returns the tip text for this property.
KnowledgeFlow - Class in weka.gui.beans: Startup class for the KnowledgeFlow.
KnowledgeFlow() - Constructor for class weka.gui.beans.KnowledgeFlow
KnowledgeFlowApp - Class in weka.gui.beans: Main GUI class for the KnowledgeFlow.
KnowledgeFlowApp(boolean) - Constructor for class weka.gui.beans.KnowledgeFlowApp: Creates a new KnowledgeFlowApp instance.
KnowledgeFlowApp.KFPerspective - Interface in weka.gui.beans: Interface for perspectives.
KnowledgeFlowApp.MainKFPerspective - Class in weka.gui.beans: Main Knowledge Flow perspective
KnowledgeFlowApp.MainKFPerspective() - Constructor for class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
KohonenMap - Class in weka.core.pmml.jaxbbindings: Java class for KohonenMap element declaration.
KohonenMap() - Constructor for class weka.core.pmml.jaxbbindings.KohonenMap
KOML - Class in weka.core.xml: This class is a helper class for XML serialization using KOML .
KOML() - Constructor for class weka.core.xml.KOML
komlToBinary(String, String) - Static method in class weka.core.xml.SerialUIDChanger: converts a KOML file into a binary one
KOMLV - Static variable in class weka.gui.beans.SerializedModelSaver
KStar - Class in weka.classifiers.lazy: K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function.
KStar() - Constructor for class weka.classifiers.lazy.KStar
KStarCache - Class in weka.classifiers.lazy.kstar: A class representing the caching system used to keep track of each attribute value and its corresponding scale factor or stop parameter.
KStarCache() - Constructor for class weka.classifiers.lazy.kstar.KStarCache
KStarCache.CacheTable - Class in weka.classifiers.lazy.kstar: A custom hashtable class to support the caching system.
KStarCache.CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
KStarCache.CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
KStarCache.TableEntry - Class in weka.classifiers.lazy.kstar: Hashtable collision list.
KStarCache.TableEntry(int, double, double, double, KStarCache.TableEntry) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.TableEntry: Constructor
KStarConstants - Interface in weka.classifiers.lazy.kstar
KStarNominalAttribute - Class in weka.classifiers.lazy.kstar: A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.
KStarNominalAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNominalAttribute: Constructor
KStarNumericAttribute - Class in weka.classifiers.lazy.kstar: A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.
KStarNumericAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNumericAttribute: Constructor
KStarWrapper - Class in weka.classifiers.lazy.kstar
KStarWrapper() - Constructor for class weka.classifiers.lazy.kstar.KStarWrapper
kthSmallestValue(Attribute, int) - Method in class weka.core.Instances: Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int, int) - Method in class weka.core.Instances: Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int[], int) - Static method in class weka.core.Utils: Returns the kth-smallest value in the array.
kthSmallestValue(double[], int) - Static method in class weka.core.Utils: Returns the kth-smallest value in the array
KValueTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property

L

LabeledItemSet - Class in weka.associations

Class for storing a set of items together with a class label.

LabeledItemSet(int, int) - Constructor for class weka.associations.LabeledItemSet

Constructor

LABELS - Static variable in class weka.core.json.JSONInstances

the labels attribute.

labelsTipText() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns the tip text for this property

labelTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns the tip text for this property.

LAGDHillClimber - Class in weka.classifiers.bayes.net.search.local

This Bayes Network learning algorithm uses a Look Ahead Hill Climbing algorithm called LAGD Hill Climbing.

LAGDHillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.LAGDHillClimber

lambdaTipText() - Method in class weka.classifiers.functions.SGD

Returns the tip text for this property

lambdaTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

lambdaTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the tip text for this property

laplaceProb(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class over all bags with Laplace correction.

laplaceProb(int, int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class for given bag.

last() - Method in class weka.core.neighboursearch.covertrees.Stack

Returns the last element in the stack.

LAST - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner

use the last attribute as class.

lastActionMsg() - Method in class weka.classifiers.bayes.net.EditableBayesNet

get message representing the last action performed on the network

lastElement() - Method in class weka.core.FastVector

Deprecated. Returns the last element of the vector.

lastElement() - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Returns the last component of the list.

lastIndexOf(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Returns the index of the last occurrence of elem.

lastIndexOf(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Searches backwards for elem, starting from the specified index, and returns an index to it.

lastInstance() - Method in class weka.core.Instances

Returns the last instance in the set.

launch() - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin

Gets called when the user clicks the button or selects this plugin's entry from the popup menu.

launch() - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin

Gets called when the user clicks the button or selects this plugin's entry from the popup menu.

launchNext(int, int) - Method in class weka.experiment.RemoteExperiment

Launch a sub experiment on a remote host

layoutCompleted(LayoutCompleteEvent) - Method in class weka.classifiers.bayes.net.GUI

This method is an implementation for LayoutCompleteEventListener class.

layoutCompleted(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.GraphVisualizer

This method is an implementation for LayoutCompleteEventListener class.

layoutCompleted(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutCompleteEventListener

LayoutCompleteEvent - Class in weka.gui.graphvisualizer

This is an event which is fired by a LayoutEngine once a LayoutEngine finishes laying out the graph, so that the Visualizer can repaint the screen to show the changes.

LayoutCompleteEvent(Object) - Constructor for class weka.gui.graphvisualizer.LayoutCompleteEvent

LayoutCompleteEventListener - Interface in weka.gui.graphvisualizer

This interface should be implemented by any class which needs to receive LayoutCompleteEvents from the LayoutEngine.

LayoutEngine - Interface in weka.gui.graphvisualizer

This interface class has been added to facilitate the addition of other layout engines to this package.

layoutGraph(ArrayList<Integer>, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet

set positions of all nodes

layoutGraph() - Method in class weka.gui.graphvisualizer.GraphVisualizer

This method lays out the graph by calling the LayoutEngine's layoutGraph() method.

layoutGraph() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

This method does a complete layout of the graph which includes removing cycles, assigning levels to nodes, reducing edge crossings and laying out the vertices horizontally for better visibility.

layoutGraph() - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method lays out the graph for better visualization

lbl - Variable in class weka.gui.graphvisualizer.GraphNode

ID and label for the node

LCURLY - Static variable in interface weka.core.json.sym

LE - Static variable in interface weka.core.mathematicalexpression.sym

LE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

LEAF_MAJ_CLASS - Static variable in class weka.classifiers.trees.HoeffdingTree

LEAF_NB - Static variable in class weka.classifiers.trees.HoeffdingTree

LEAF_NB_ADAPTIVE - Static variable in class weka.classifiers.trees.HoeffdingTree

leafForInstance(Instance, SplitNode, String) - Method in class weka.classifiers.trees.ht.HNode

Return the leaf that the supplied instance ends up at

leafForInstance(Instance, SplitNode, String) - Method in class weka.classifiers.trees.ht.SplitNode

LeafNode - Class in weka.classifiers.trees.ht

Leaf node in a HoeffdingTree

LeafNode() - Constructor for class weka.classifiers.trees.ht.LeafNode

Construct an empty leaf node

LeafNode(HNode, SplitNode, String) - Constructor for class weka.classifiers.trees.ht.LeafNode

Construct a leaf node with the given actual node, parent and parent branch

leafPredictionStrategyTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

LearningNode - Interface in weka.classifiers.trees.ht

Marker interface for a node that can be updated with incoming instances in a HoeffdingTree.

LearningRateResultProducer - Class in weka.experiment

Tells a sub-ResultProducer to reproduce the current run for varying sized subsamples of the dataset.

LearningRateResultProducer() - Constructor for class weka.experiment.LearningRateResultProducer

learningRateTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

learningRateTipText() - Method in class weka.classifiers.functions.SGD

Returns the tip text for this property

learningRateTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

leaveOneOutCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

LeaveOneOutCV returns the accuracy calculated using Leave One Out cross validation.

LED24 - Class in weka.datagenerators.classifiers.classification

This generator produces data for a display with 7 LEDs.

LED24() - Constructor for class weka.datagenerators.classifiers.classification.LED24

initializes the generator with default values

LEFT_PARENTHESES - Variable in class weka.experiment.ResultMatrix

the left parentheses for enumerating cols/rows.

leftNode() - Method in class weka.classifiers.trees.m5.RuleNode

Get the left child of this node

leftSide(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split

Prints left side of condition.

leftSide(Instances) - Method in class weka.classifiers.trees.j48.C45Split

Prints left side of condition..

leftSide(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Prints left side of condition satisfied by instances.

leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Does nothing because no condition has to be satisfied.

leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit

Prints left side of condition..

leftSide(Instances) - Method in class weka.classifiers.trees.j48.NoSplit

Does nothing because no condition has to be satisfied.

leftSide(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit

Returns name of splitting attribute (left side of condition).

LegendPanel - Class in weka.gui.visualize

This panel displays legends for a list of plots.

LegendPanel() - Constructor for class weka.gui.visualize.LegendPanel

Constructor

length - Variable in class weka.core.neighboursearch.covertrees.Stack

The number of elements in the stack.

Level - Class in weka.core.pmml.jaxbbindings

Java class for Level element declaration.

Level() - Constructor for class weka.core.pmml.jaxbbindings.Level

leverageForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet

Outputs the leverage for a rule.

LibSVMLoader - Class in weka.core.converters

Reads a source that is in libsvm format.

For more information about libsvm see:

http://www.csie.ntu.edu.tw/~cjlin/libsvm/

LibSVMLoader() - Constructor for class weka.core.converters.LibSVMLoader

LibSVMSaver - Class in weka.core.converters

Writes to a destination that is in libsvm format.

For more information about libsvm see:

http://www.csie.ntu.edu.tw/~cjlin/libsvm/

Valid options are:

LibSVMSaver() - Constructor for class weka.core.converters.LibSVMSaver

Constructor

LIFT_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

attribute name: Lift

LiftData - Class in weka.core.pmml.jaxbbindings

Java class for LiftData element declaration.

LiftData() - Constructor for class weka.core.pmml.jaxbbindings.LiftData

liftForRule(AprioriItemSet, AprioriItemSet, int) - Method in class weka.associations.AprioriItemSet

Outputs the lift for a rule.

LiftGraph - Class in weka.core.pmml.jaxbbindings

Java class for LiftGraph element declaration.

LiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.LiftGraph

likelihoodThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost

Returns the tip text for this property

LINE - Static variable in class weka.gui.visualize.VisualizePanelEvent

LINEAR - Static variable in class weka.classifiers.lazy.LWL

The available kernel weighting methods.

LinearKernelType - Class in weka.core.pmml.jaxbbindings

Java class for LinearKernelType element declaration.

LinearKernelType() - Constructor for class weka.core.pmml.jaxbbindings.LinearKernelType

LinearNNSearch - Class in weka.core.neighboursearch

Class implementing the brute force search algorithm for nearest neighbour search.

LinearNNSearch() - Constructor for class weka.core.neighboursearch.LinearNNSearch

Constructor.

LinearNNSearch(Instances) - Constructor for class weka.core.neighboursearch.LinearNNSearch

Constructor that uses the supplied set of instances.

LinearNorm - Class in weka.core.pmml.jaxbbindings

Java class for LinearNorm element declaration.

LinearNorm() - Constructor for class weka.core.pmml.jaxbbindings.LinearNorm

LinearRegression - Class in weka.classifiers.functions

Class for using linear regression for prediction.

LinearRegression() - Constructor for class weka.classifiers.functions.LinearRegression

LinearRegression - Class in weka.core.matrix

Class for performing (ridged) linear regression using Tikhonov regularization.

LinearRegression(Matrix, Matrix, double) - Constructor for class weka.core.matrix.LinearRegression

Performs a (ridged) linear regression.

LinearRegression(Matrix, Matrix, double[], double) - Constructor for class weka.core.matrix.LinearRegression

Performs a weighted (ridged) linear regression.

LinearUnit - Class in weka.classifiers.functions.neural

This can be used by the neuralnode to perform all it's computations (as a Linear unit).

LinearUnit() - Constructor for class weka.classifiers.functions.neural.LinearUnit

lineWrap(String, int) - Static method in class weka.core.Utils

Implements simple line breaking.

LINKFUNCTION - Enum in weka.core.pmml.jaxbbindings

Java class for LINK-FUNCTION.

linkTypeTipText() - Method in class weka.clusterers.HierarchicalClusterer

LINUX_BROWSERS - Static variable in class weka.gui.BrowserHelper

Linux/Unix binaries to look for

listCapabilities(Capabilities) - Static method in class weka.gui.PropertySheetPanel

returns a comma-separated list of all the capabilities.

listOptions() - Method in class weka.associations.Apriori

Returns an enumeration describing the available options.

listOptions() - Method in class weka.associations.CheckAssociator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.associations.FilteredAssociator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.associations.FPGrowth

Returns an enumeration describing the available options.

listOptions() - Method in class weka.associations.SingleAssociatorEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.BestFirst

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.CfsSubsetEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.CheckAttributeSelection

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.CorrelationAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.GreedyStepwise

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.OneRAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.PrincipalComponents

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.Ranker

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.AbstractClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.BayesNet

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.NaiveBayes

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.K2

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.K2

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.BVDecompose

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.CheckClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.CheckSource

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns an enumeration of all the available options..

listOptions() - Method in class weka.classifiers.evaluation.output.prediction.CSV

Returns an enumeration of all the available options..

listOptions() - Method in class weka.classifiers.functions.GaussianProcesses

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.LinearRegression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.Logistic

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SGD

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SGDText

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SimpleLogistic

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SMO

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SMOreg

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.CachedKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.CheckKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.PolyKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.Puk

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.RBFKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.supportVector.RegSMO

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.VotedPerceptron

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.IBk

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.KStar

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.LWL

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AdaBoostM1

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AdditiveRegression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Bagging

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.CVParameterSelection

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.FilteredClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.LogitBoost

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.MultiClassClassifier

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.meta.MultiScheme

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.RandomSubSpace

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Stacking

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Vote

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.misc.SerializedClassifier

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.rules.DecisionTable

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.rules.JRip

Returns an enumeration describing the available options Valid options are:

listOptions() - Method in class weka.classifiers.rules.OneR

Returns an enumeration describing the available options..

listOptions() - Method in class weka.classifiers.rules.PART

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.SingleClassifierEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.HoeffdingTree

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.J48

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.LMT

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.m5.M5Base

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.trees.M5P

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.trees.RandomForest

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.RandomTree

Lists the command-line options for this classifier.

listOptions() - Method in class weka.classifiers.trees.REPTree

Lists the command-line options for this classifier.

listOptions() - Method in class weka.clusterers.AbstractClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.Canopy

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.CheckClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.Cobweb

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.EM

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.FarthestFirst

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.FilteredClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.HierarchicalClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.clusterers.RandomizableClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.SimpleKMeans

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.SingleClustererEnhancer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.Check

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.CheckGOE

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.CheckOptionHandler

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.CheckScheme

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.AbstractFileSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.ArffSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.C45Saver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.CSVLoader

listOptions() - Method in class weka.core.converters.CSVSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.DatabaseLoader

Lists the available options

listOptions() - Method in class weka.core.converters.DatabaseSaver

Lists the available options.

listOptions() - Method in class weka.core.converters.JSONSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.LibSVMSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.MatlabSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.SVMLightSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.TextDirectoryLoader

Lists the available options

listOptions() - Method in class weka.core.converters.XRFFSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.FindWithCapabilities

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.Javadoc

Returns an enumeration describing the available options.

ListOptions - Class in weka.core

Lists the options of an OptionHandler

ListOptions() - Constructor for class weka.core.ListOptions

listOptions() - Method in class weka.core.ListOptions

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.MinkowskiDistance

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.BallTree

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.CoverTree

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.KDTree

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.LinearNNSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.NormalizableDistance

Returns an enumeration describing the available options.

listOptions() - Method in interface weka.core.OptionHandler

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.OptionHandlerJavadoc

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.stemmers.SnowballStemmer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.TechnicalInformationHandlerJavadoc

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.TestInstances

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.tokenizers.NGramTokenizer

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.tokenizers.Tokenizer

Returns an enumeration of all the available options..

listOptions() - Method in class weka.datagenerators.ClassificationGenerator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.classification.LED24

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.regression.Expression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.ClusterDefinition

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.ClusterGenerator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.DataGenerator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.datagenerators.RegressionGenerator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.estimators.CheckEstimator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.estimators.Estimator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.experiment.AveragingResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.ClassifierSplitEvaluator

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.CrossValidationResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.CSVResultListener

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.DatabaseResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.experiment.Experiment

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.InstanceQuery

Returns an enumeration describing the available options

listOptions() - Method in class weka.experiment.LearningRateResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.PairedTTester

Lists options understood by this object.

listOptions() - Method in class weka.experiment.RandomSplitResultProducer

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.RegressionSplitEvaluator

Returns an enumeration describing the available options..

listOptions() - Method in class weka.experiment.ResultMatrix

Returns an enumeration of all the available options..

listOptions() - Method in class weka.filters.CheckSource

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.MultiFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.SimpleFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.AddClassification

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.ClassOrder

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.Discretize

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.PartitionMembership

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.instance.Resample

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets an enumeration describing the available options..

listOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Add

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AddID

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns an enumeration describing the available options

listOptions() - Method in class weka.filters.unsupervised.attribute.AddUserFields

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Returns an enumeration describing the available options

listOptions() - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Copy

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Discretize

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MathExpression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToString

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Remove

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveByName

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

listOptions() - Method in class weka.filters.unsupervised.attribute.Reorder

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

listOptions() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.Randomize

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets an enumeration describing the available options..

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Gets an enumeration describing the available options..

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.Resample

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.gui.explorer.AbstractPlotInstances

Returns an enumeration of all the available options.

listOptions() - Method in class weka.gui.Main

Gets an enumeration describing the available options.

listOptions() - Method in class weka.gui.scripting.Script

Returns an enumeration describing the available options.

ListSelectorDialog - Class in weka.gui

A dialog to present the user with a list of items, that the user can make a selection from, or cancel the selection.

ListSelectorDialog(Frame, JList) - Constructor for class weka.gui.ListSelectorDialog

Create the list selection dialog.

listStemmers() - Static method in class weka.core.stemmers.SnowballStemmer

returns an enumeration over all currently stored stemmer names.

LMT - Class in weka.classifiers.trees

Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.

LMT() - Constructor for class weka.classifiers.trees.LMT

Creates an instance of LMT with standard options

LMTNode - Class in weka.classifiers.trees.lmt

Class for logistic model tree structure.

LMTNode(ModelSelection, int, boolean, boolean, int, double, boolean, NominalToBinary) - Constructor for class weka.classifiers.trees.lmt.LMTNode

Constructor for logistic model tree node.

lnFactorial(int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

Fast computation of ln(n!) for non-negative ints negative ints are passed on to the general gamma-function based version in weka.core.SpecialFunctions if the current n value is higher than any previous one, the cache is extended and filled to cover it the common case is reduced to a simple array lookup

lnFactorial(double) - Static method in class weka.core.SpecialFunctions

Returns natural logarithm of factorial using gamma function.

lnFunc(double) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit

Help method for computing entropy.

lnFunc(double) - Static method in class weka.core.ContingencyTables

Help method for computing entropy.

lnGamma(double) - Static method in class weka.core.Statistics

Returns natural logarithm of gamma function.

LNormTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

LNormTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

lnsrch(double[], double[], double[], double, boolean[], double[][], Optimization.DynamicIntArray) - Method in class weka.core.Optimization

Find a new point x in the direction p from a point xold at which the value of the function has decreased sufficiently, the positive definiteness of B matrix (approximation of the inverse of the Hessian) is preserved and no bound constraints are violated.

load(InputStream) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

load(String) - Method in class weka.gui.beans.FlowRunner

Load a serialized KnowledgeFlow (either binary or xml)

load(File) - Static method in class weka.gui.scripting.ScriptUtils

Tries to load the file and return its content.

loadBinary(String) - Method in class weka.gui.beans.FlowRunner

Load a binary serialized KnowledgeFlow

loadCheck(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageManager

Check whether a package should be loaded or not.

Loader - Interface in weka.core.converters

Interface to something that can load Instances from an input source in some format.

Loader - Class in weka.gui.beans

Loads data sets using weka.core.converter classes

Loader() - Constructor for class weka.gui.beans.Loader

Loader - Class in weka.gui

This class is for loading resources from a JAR archive.

Loader(String) - Constructor for class weka.gui.Loader

initializes the object

Loader.StructureNotReadyException - Exception in weka.core.converters

Exception that implementers can throw from getStructure() when they have not been configured sufficiently in order to read the structure (or data).

Loader.StructureNotReadyException(String) - Constructor for exception weka.core.converters.Loader.StructureNotReadyException

LOADER_DIALOG - Static variable in class weka.gui.ConverterFileChooser

the loader dialog.

LoaderBeanInfo - Class in weka.gui.beans

Bean info class for the loader bean

LoaderBeanInfo() - Constructor for class weka.gui.beans.LoaderBeanInfo

LoaderCustomizer - Class in weka.gui.beans

GUI Customizer for the loader bean

LoaderCustomizer() - Constructor for class weka.gui.beans.LoaderCustomizer

loadFile(String, AbstractFileLoader...) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

loads the specified file

loadFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

loads the specified file into the table

loadFromFile(String) - Static method in class weka.core.Debug

deserializes the content of the file and returns it, null if an error occurred.

loadIcons(String, String) - Method in class weka.gui.beans.BeanVisual

Loads static and animated versions of a beans icons.

loadLayout(File, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp

Load a layout from a file.

loadLayout(InputStream, boolean, String) - Method in class weka.gui.beans.KnowledgeFlowApp

Load a flow file from an input stream.

loadLayout(Reader, boolean, String) - Method in class weka.gui.beans.KnowledgeFlowApp

Load a flow file from a reader.

loadModel() - Method in class weka.gui.beans.Classifier

loadModel() - Method in class weka.gui.beans.Clusterer

loadPackages(boolean) - Static method in class weka.core.WekaPackageManager

Load all packages

loadPackages(boolean, boolean, boolean) - Static method in class weka.core.WekaPackageManager

Load all packages

loadProperties() - Static method in class weka.gui.beans.BeansProperties

Loads KnowledgeFlow properties and any plugins (adds jars to the classpath)

loadProperties() - Static method in class weka.gui.beans.KnowledgeFlowApp

Loads KnowledgeFlow properties and any plugins (adds jars to the classpath)

loadXML(String) - Method in class weka.gui.beans.FlowRunner

Load an XML serialized KnowledgeFlow

locallyPredictiveTipText() - Method in class weka.attributeSelection.CfsSubsetEval

Returns the tip text for this property

LocalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.local

The ScoreBasedSearchAlgorithm class supports Bayes net structure search algorithms that are based on maximizing scores (as opposed to for example conditional independence based search algorithms).

LocalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

default constructor

LocalScoreSearchAlgorithm(BayesNet, Instances) - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

constructor

LocalTransformations - Class in weka.core.pmml.jaxbbindings

Java class for LocalTransformations element declaration.

LocalTransformations() - Constructor for class weka.core.pmml.jaxbbindings.LocalTransformations

locateIndex(int) - Method in class weka.core.pmml.SparseArray

Locates the greatest index that is not greater than the given index.

locateIndex(int) - Method in class weka.core.SparseInstance

Locates the greatest index that is not greater than the given index.

log(String) - Method in class weka.core.Debug

prints the given message with level INFO

log(Level, String) - Method in class weka.core.Debug

prints the given message with the specified level and an empty sourceclass

log(Level, String, String) - Method in class weka.core.Debug

prints the given message with the specified level

log(Level, String, String, String) - Method in class weka.core.Debug

prints the given message with the specified level

log(Level, String) - Method in class weka.core.Debug.Log

logs the given message

log(Level, String, String) - Method in class weka.core.Debug.Log

prints the given message with the specified level

log(Level, String, String, String) - Method in class weka.core.Debug.Log

prints the given message with the specified level

log(String) - Method in class weka.core.Debug.SimpleLog

logs the given message to the file

log(Logger.Level, String) - Static method in class weka.core.logging.Logger

Logs the given message under the given level.

log(Logger.Level, Throwable) - Static method in class weka.core.logging.Logger

Logs the given message under the given level.

LOG - Static variable in interface weka.core.mathematicalexpression.sym

LOG - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

LOG2 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

log2 - Static variable in class weka.core.ContingencyTables

The natural logarithm of 2

log2 - Static variable in class weka.core.Utils

The natural logarithm of 2.

log2(double) - Static method in class weka.core.Utils

Returns the logarithm of a for base 2.

log2Binomial(double, double) - Static method in class weka.core.SpecialFunctions

Returns base 2 logarithm of binomial coefficient using gamma function.

log2Multinomial(double, double[]) - Static method in class weka.core.SpecialFunctions

Returns base 2 logarithm of multinomial using gamma function.

log2MultipleHypergeometric(double[][]) - Static method in class weka.core.ContingencyTables

Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.

Log2PI - Static variable in class weka.estimators.MultivariateGaussianEstimator

Log of twice number pi: log(2*pi).

logDensity(Instance, double) - Method in interface weka.classifiers.ConditionalDensityEstimator

Returns natural logarithm of density estimate for given value based on given instance.

logDensity(Instance, double) - Method in class weka.classifiers.functions.GaussianProcesses

Returns natural logarithm of density estimate for given value based on given instance.

logDensity(Instance, double) - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns natural logarithm of density estimate for given value based on given instance.

logDensity(double[]) - Method in interface weka.estimators.MultivariateEstimator

Returns the natural logarithm of the density estimate at the given point.

logDensity(double[]) - Method in class weka.estimators.MultivariateGaussianEstimator

Returns the log likelihood of density value for the Multivariate distribution

logDensity(double) - Method in interface weka.estimators.UnivariateDensityEstimator

Returns the natural logarithm of the density estimate at the given point.

logDensity(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Returns the natural logarithm of the density estimate at the given point.

logDensity(double) - Method in class weka.estimators.UnivariateKernelEstimator

Returns the natural logarithm of the density estimate at the given point.

logDensity(double) - Method in class weka.estimators.UnivariateNormalEstimator

Returns the natural logarithm of the density estimate at the given point.

logDensityForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer

Computes the density for a given instance.

logDensityForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer

Computes the density for a given instance.

logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer

Computes the log of the conditional density (per cluster) for a given instance.

logDensityPerClusterForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer

Computes the log of the conditional density (per cluster) for a given instance.

logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.EM

Computes the log of the conditional density (per cluster) for a given instance.

logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.MakeDensityBasedClusterer

Computes the log of the conditional density (per cluster) for a given instance.

Logger - Class in weka.core.logging

Abstract superclass for all loggers.

Logger() - Constructor for class weka.core.logging.Logger

Initializes the logger.

Logger - Interface in weka.gui

Interface for objects that display log (permanent historical) and status (transient) messages.

Logger.Level - Enum in weka.core.logging

The logging level.

LogHandler - Interface in weka.core

Interface to something that can output messages to a log

Logistic - Class in weka.classifiers.functions

Class for building and using a multinomial logistic regression model with a ridge estimator.

There are some modifications, however, compared to the paper of leCessie and van Houwelingen(1992):

If there are k classes for n instances with m attributes, the parameter matrix B to be calculated will be an m*(k-1) matrix.

The probability for class j with the exception of the last class is

Pj(Xi) = exp(XiBj)/((sum[j=1..(k-1)]exp(Xi*Bj))+1)

The last class has probability

1-(sum[j=1..(k-1)]Pj(Xi))
= 1/((sum[j=1..(k-1)]exp(Xi*Bj))+1)

The (negative) multinomial log-likelihood is thus:

L = -sum[i=1..n]{
sum[j=1..(k-1)](Yij * ln(Pj(Xi)))
+(1 - (sum[j=1..(k-1)]Yij))
* ln(1 - sum[j=1..(k-1)]Pj(Xi))
} + ridge * (B^2)

In order to find the matrix B for which L is minimised, a Quasi-Newton Method is used to search for the optimized values of the m*(k-1) variables.

Logistic() - Constructor for class weka.classifiers.functions.Logistic

LogisticBase - Class in weka.classifiers.trees.lmt

Base/helper class for building logistic regression models with the LogitBoost algorithm.

LogisticBase() - Constructor for class weka.classifiers.trees.lmt.LogisticBase

Constructor that creates LogisticBase object with standard options.

LogisticBase(int, boolean, boolean) - Constructor for class weka.classifiers.trees.lmt.LogisticBase

Constructor to create LogisticBase object.

LogisticProducerHelper - Class in weka.classifiers.pmml.producer

Helper class for producing PMML for a Logistic classifier.

LogisticProducerHelper() - Constructor for class weka.classifiers.pmml.producer.LogisticProducerHelper

LogitBoost - Class in weka.classifiers.meta

Class for performing additive logistic regression.

LogitBoost() - Constructor for class weka.classifiers.meta.LogitBoost

Constructor.

logJointDensitiesForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer

Returns the logs of the joint densities for a given instance.

logJointDensitiesForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer

Returns the logs of the joint densities for a given instance.

LOGLOSS - Static variable in class weka.classifiers.functions.SGD

the log loss function.

LOGLOSS - Static variable in class weka.classifiers.functions.SGDText

the log loss function.

logMessage(String) - Method in class weka.gui.beans.FlowRunner.SimpleLogger

logMessage(String) - Method in class weka.gui.beans.LogPanel

Sends the supplied message to the log area.

logMessage(String) - Method in interface weka.gui.Logger

Sends the supplied message to the log area.

logMessage(String) - Method in class weka.gui.LogPanel

Sends the supplied message to the log area.

logMessage(String) - Method in class weka.gui.SysErrLog

Sends the supplied message to the log area.

LogPanel - Class in weka.gui.beans

Class for displaying a status area (made up of a variable number of lines) and a log area.

LogPanel() - Constructor for class weka.gui.beans.LogPanel

LogPanel - Class in weka.gui

This panel allows log and status messages to be posted.

LogPanel() - Constructor for class weka.gui.LogPanel

Creates the log panel with no task monitor and the log always visible.

LogPanel(WekaTaskMonitor) - Constructor for class weka.gui.LogPanel

Creates the log panel with a task monitor, where the log is hidden.

LogPanel(WekaTaskMonitor, boolean) - Constructor for class weka.gui.LogPanel

Creates the log panel, possibly with task monitor, where the log is optionally hidden.

LogPanel(WekaTaskMonitor, boolean, boolean, boolean) - Constructor for class weka.gui.LogPanel

Creates the log panel, possibly with task monitor, where the either the log is optionally hidden or the status (having both hidden is not allowed).

logPSI - Static variable in class weka.core.matrix.Maths

The constant - log( sqrt(2 pi) )

logs2probs(double[]) - Static method in class weka.core.Utils

Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.

logScore(int, int) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Gets the log score contribution of this distribution

logScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

logScore returns the log of the quality of a network (e.g.

logScore(int, int) - Method in interface weka.classifiers.bayes.net.search.local.Scoreable

Returns log-score

logSystemInfo() - Method in class weka.core.Debug.Log

a convenience method for dumping the current system info in the log file

logSystemInfo() - Method in class weka.core.Debug.SimpleLog

a convenience method for dumping the current system info in the log file

LogWindow - Class in weka.gui

Frame that shows the output from stdout and stderr.

LogWindow() - Constructor for class weka.gui.LogWindow

creates the frame

LogWriter - Interface in weka.gui.beans

Interface to be implemented by classes that should be able to write their own output to the Weka logger.

LONG - Static variable in class weka.experiment.DatabaseUtils

Type mapping for LONG used for reading experiment results.

LookAndFeel - Class in weka.gui

A little helper class for setting the Look and Feel of the user interface.

LookAndFeel() - Constructor for class weka.gui.LookAndFeel

lookupCacheSizeTipText() - Method in class weka.attributeSelection.BestFirst

Returns the tip text for this property

LOSS_STRING - Variable in class weka.experiment.ResultMatrix

loss string.

lossFunctionTipText() - Method in class weka.classifiers.functions.SGD

Returns the tip text for this property

lossFunctionTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

LovinsStemmer - Class in weka.core.stemmers

A stemmer based on the Lovins stemmer, described here:

Julie Beth Lovins (1968).

LovinsStemmer() - Constructor for class weka.core.stemmers.LovinsStemmer

LOW_MEMORY_MINIMUM - Static variable in class weka.core.Memory

lowerBoundMinSupportTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

lowerBoundMinSupportTipText() - Method in class weka.associations.FPGrowth

Returns the tip text for this property

lowercaseTokensTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

lowercaseTokensTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

lowerCaseTokensTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

lowerNumericBoundIsOpen() - Method in class weka.core.Attribute

Returns whether the lower numeric bound of the attribute is open.

lowerSizeTipText() - Method in class weka.experiment.LearningRateResultProducer

Returns the tip text for this property

LPAREN - Static variable in interface weka.core.mathematicalexpression.sym

LPAREN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

LSQUARE - Static variable in interface weka.core.json.sym

LT - Static variable in interface weka.core.mathematicalexpression.sym

LT - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

lu() - Method in class weka.core.matrix.Matrix

LU Decomposition

LUDecomposition - Class in weka.core.matrix

LU Decomposition.

LUDecomposition() - Method in class weka.core.Matrix

Deprecated. Performs a LUDecomposition on the matrix.

LUDecomposition(Matrix) - Constructor for class weka.core.matrix.LUDecomposition

LU Decomposition

LWL - Class in weka.classifiers.lazy

Locally weighted learning.

LWL() - Constructor for class weka.classifiers.lazy.LWL

Constructor.

M

M5Base - Class in weka.classifiers.trees.m5

M5Base.

M5Base() - Constructor for class weka.classifiers.trees.m5.M5Base

Constructor

M5P - Class in weka.classifiers.trees

M5Base.

M5P() - Constructor for class weka.classifiers.trees.M5P

Creates a new M5P instance.

M5Rules - Class in weka.classifiers.rules

Generates a decision list for regression problems using separate-and-conquer.

M5Rules() - Constructor for class weka.classifiers.rules.M5Rules

Constructor

m_ADNodes - Variable in class weka.classifiers.bayes.net.VaryNode

list of ADNode children

m_alpha - Variable in class weka.classifiers.functions.supportVector.RegOptimizer

alpha and alpha* arrays containing weights for solving dual problem

m_alpha - Variable in class weka.classifiers.trees.lmt.LMTNode

Alpha-value (for pruning) at the node

m_alphaStar - Variable in class weka.classifiers.functions.supportVector.RegOptimizer

m_alwaysDisplayPointsOfThisSize - Variable in class weka.gui.visualize.PlotData2D

If the shape size of a point equals this size then always plot it (i.e.

M_AVERAGE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_children - Variable in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

m_classDistribution - Variable in class weka.classifiers.trees.ht.HNode

Class distribution at this node

m_col - Variable in class weka.gui.treevisualizer.NamedColor

The actual color object

m_cols - Variable in class weka.gui.treevisualizer.Colors

The array with all the colors input

m_CoordCount - Variable in class weka.core.neighboursearch.PerformanceStats

The number of coordinates looked at for the current/last query.

m_count - Variable in class weka.classifiers.functions.SGDText.Count

m_customColour - Variable in class weka.gui.visualize.PlotData2D

m_defaultExpression - Static variable in class weka.filters.unsupervised.attribute.MathExpression

The default modification expression

M_DELETE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

Missing value handling mode

m_displayAllPoints - Variable in class weka.gui.visualize.PlotData2D

Display all points (ie.

m_Distributions - Variable in class weka.classifiers.bayes.BayesNet

The attribute estimators containing CPTs.

m_doNotLoadList - Static variable in class weka.core.WekaPackageManager

The set of packages that the user has requested not to load

m_End - Variable in class weka.core.neighboursearch.balltrees.BallNode

The end index of the portion of the master index array, which stores indices of the instances/points the node contains.

m_End - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

The end index of the portion of the master index array, which stores indices of the instances/points the node contains.

m_experimentFinished - Variable in class weka.experiment.RemoteExperimentEvent

True if a remote experiment has finished

m_hidden_index - Variable in class weka.gui.beans.InteractiveTableModel

Index of the hidden column

m_indexVal - Variable in class weka.gui.visualize.AttributePanelEvent

The index for the new attribute

m_initialPackageLoadingInProcess - Static variable in class weka.core.WekaPackageManager

Package loading in progress?

m_iNode - Variable in class weka.classifiers.bayes.net.VaryNode

index of the node varied

m_Instances - Variable in class weka.classifiers.bayes.BayesNet

The dataset header for the purposes of printing out a semi-intelligible model

m_Instances - Variable in class weka.classifiers.bayes.net.ADNode

list of Instance children (either m_Instances or m_VaryNodes is instantiated)

m_L - Variable in class weka.classifiers.functions.GaussianProcesses

(negative) covariance matrix in symmetric matrix representation

m_Left - Variable in class weka.core.neighboursearch.balltrees.BallNode

The left child of the node.

m_Left - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

left subtree; contains instances with smaller or equal to split value.

m_logMessage - Variable in class weka.experiment.RemoteExperimentEvent

A log type message

m_MaxC - Variable in class weka.core.neighboursearch.PerformanceStats

The min and max coordinates(attributes) looked at per query.

M_MAXDIFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_MaxP - Variable in class weka.core.neighboursearch.PerformanceStats

The min and max data points looked for a query by the NNS algorithm.

m_messageString - Variable in class weka.experiment.RemoteExperimentEvent

The message

m_MinC - Variable in class weka.core.neighboursearch.PerformanceStats

The min and max coordinates(attributes) looked at per query.

m_MinP - Variable in class weka.core.neighboursearch.PerformanceStats

The min and max data points looked for a query by the NNS algorithm.

m_name - Variable in class weka.gui.treevisualizer.NamedColor

The name of the color

m_nCount - Variable in class weka.classifiers.bayes.net.ADNode

count

m_nMCV - Variable in class weka.classifiers.bayes.net.VaryNode

most common value

m_nNodes - Variable in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

nodes of the Bayes net in this junction node

m_NodeNumber - Variable in class weka.core.neighboursearch.balltrees.BallNode

The node number/id.

m_NodeNumber - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

node number (only for debug).

m_NodeRanges - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

lowest and highest value and width (= high - low) for each dimension.

m_NodesRectBounds - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

The lo and high bounds of the hyper rectangle described by the node.

m_noPackageMetaDataAvailable - Static variable in class weka.core.WekaPackageManager

M_NORMAL - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_nStartNode - Variable in class weka.classifiers.bayes.net.ADNode

first node in VaryNode array

m_numIncorrectModel - Variable in class weka.classifiers.trees.lmt.LMTNode

Weighted number of training examples currently misclassified by the logistic model at the node

m_numIncorrectTree - Variable in class weka.classifiers.trees.lmt.LMTNode

Weighted number of training examples currently misclassified by the subtree rooted at the node

m_NumInstances - Variable in class weka.core.neighboursearch.balltrees.BallNode

The number of instances/points in the node.

m_numParameters - Variable in class weka.classifiers.trees.m5.RuleNode

the number of paramters in the chosen model for this node---either the subtree model or the linear model.

m_offline - Static variable in class weka.core.WekaPackageManager

Operating offline?

m_OutputFormat - Variable in class weka.core.Debug.Clock

the format of the output

m_outputTypes - Variable in class weka.core.Debug.DBO

range of outputtyp

m_parentBranch - Variable in class weka.classifiers.trees.ht.LeafNode

Parent branch leading to this node

m_parentNode - Variable in class weka.classifiers.trees.ht.LeafNode

Parent split node

m_PointCount - Variable in class weka.core.neighboursearch.PerformanceStats

The number of data points looked at for the current/last query.

m_postSplitClassDistributions - Variable in class weka.classifiers.trees.ht.SplitCandidate

list of class distributions resulting from a split - 2 entries in the outer list for numeric splits and n for nominal splits

m_Right - Variable in class weka.core.neighboursearch.balltrees.BallNode

The right child of the node.

m_Right - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

right subtree; contains instances with larger than split value.

m_root - Variable in class weka.classifiers.bayes.net.MarginCalculator

m_SplitAttrib - Variable in class weka.core.neighboursearch.balltrees.BallNode

The attribute that splits this node (not always used).

m_SplitDim - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

attribute to split on.

m_splitMerit - Variable in class weka.classifiers.trees.ht.SplitCandidate

The merit of the split

m_splitTest - Variable in class weka.classifiers.trees.ht.SplitCandidate

m_SplitVal - Variable in class weka.core.neighboursearch.balltrees.BallNode

The value of m_SpiltAttrib that splits this node (not always used).

m_SplitValue - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

value to split on.

m_Start - Variable in class weka.core.neighboursearch.balltrees.BallNode

The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.

m_Start - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode

The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.

m_statusMessage - Variable in class weka.experiment.RemoteExperimentEvent

A status type message

m_SumC - Variable in class weka.core.neighboursearch.PerformanceStats

The sum of coordinates/attributes looked at for all the queries.

m_SumP - Variable in class weka.core.neighboursearch.PerformanceStats

The sum of data points looked at for all the queries.

m_SumSqC - Variable in class weka.core.neighboursearch.PerformanceStats

The squared sum of coordinates/attributes looked at for all the queries.

m_SumSqP - Variable in class weka.core.neighboursearch.PerformanceStats

The squared sum of data points looked at for all the queries.

m_theNode - Variable in class weka.classifiers.trees.ht.LeafNode

The actual node for this leaf

m_useCustomColour - Variable in class weka.gui.visualize.PlotData2D

Custom colour for this plot

m_UseWordwrap - Variable in class weka.gui.LogWindow

whether the JTextPane has wordwrap or not

m_VaryNodes - Variable in class weka.classifiers.bayes.net.ADNode

list of VaryNode children

m_verboseOn - Variable in class weka.core.Debug.DBO

enables/disables output of debug information

m_weight - Variable in class weka.classifiers.functions.SGDText.Count

m_weight - Variable in class weka.classifiers.trees.ht.WeightMass

m_weightSeenAtLastSplitEval - Variable in class weka.classifiers.trees.ht.ActiveHNode

The weight of instances seen at the last split evaluation

m_xChange - Variable in class weka.gui.visualize.AttributePanelEvent

True if the x selection changed

m_yChange - Variable in class weka.gui.visualize.AttributePanelEvent

True if the y selection changed

MahalanobisEstimator - Class in weka.estimators

Simple probability estimator that places a single normal distribution over the observed values.

MahalanobisEstimator(Matrix, double, double) - Constructor for class weka.estimators.MahalanobisEstimator

Constructor

main(String[]) - Static method in class weka.associations.Apriori

Main method.

main(String[]) - Static method in class weka.associations.AssociatorEvaluation

A test method for this class.

main(String[]) - Static method in class weka.associations.CheckAssociator

Test method for this class

main(String[]) - Static method in class weka.associations.FilteredAssociator

Main method for running this class.

main(String[]) - Static method in class weka.associations.FPGrowth

Main method.

main(String[]) - Static method in class weka.attributeSelection.AttributeSelection

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.CfsSubsetEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.CheckAttributeSelection

Test method for this class

main(String[]) - Static method in class weka.attributeSelection.CorrelationAttributeEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.GainRatioAttributeEval

Main method.

main(String[]) - Static method in class weka.attributeSelection.InfoGainAttributeEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.OneRAttributeEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.PrincipalComponents

Main method for testing this class

main(String[]) - Static method in class weka.attributeSelection.ReliefFAttributeEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Main method for testing this class.

main(String[]) - Static method in class weka.attributeSelection.WrapperSubsetEval

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.BayesNet

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayes

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomial

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesUpdateable

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.net.ADNode

for testing only

main(String[]) - Static method in class weka.classifiers.bayes.net.BayesNetGenerator

Main method

main(String[]) - Static method in class weka.classifiers.bayes.net.BIFReader

Loads the file specified as first parameter and prints it to stdout.

main(String[]) - Static method in class weka.classifiers.bayes.net.EditableBayesNet

main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.bayes.net.GUI

Main method.

main(String[]) - Static method in class weka.classifiers.bayes.net.MarginCalculator

main(String[]) - Static method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

for testing the class

main(String[]) - Static method in class weka.classifiers.BVDecompose

Test method for this class

main(String[]) - Static method in class weka.classifiers.BVDecomposeSegCVSub

Test method for this class

main(String[]) - Static method in class weka.classifiers.CheckClassifier

Test method for this class

main(String[]) - Static method in class weka.classifiers.CheckSource

Executes the tests, use "-h" to list the commandline options.

main(String[]) - Static method in class weka.classifiers.evaluation.CostCurve

Tests the CostCurve generation from the command line.

main(String[]) - Static method in class weka.classifiers.evaluation.Evaluation

A test method for this class.

main(String[]) - Static method in class weka.classifiers.Evaluation

A test method for this class.

main(String[]) - Static method in class weka.classifiers.evaluation.MarginCurve

Tests the MarginCurve generation from the command line.

main(String[]) - Static method in class weka.classifiers.evaluation.ThresholdCurve

Tests the ThresholdCurve generation from the command line.

main(String[]) - Static method in class weka.classifiers.functions.GaussianProcesses

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.LinearRegression

Generates a linear regression function predictor.

main(String[]) - Static method in class weka.classifiers.functions.Logistic

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.MultilayerPerceptron

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.SGD

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.SGDText

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegression

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.functions.SimpleLogistic

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.functions.SMO

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.SMOreg

Main method for running this classifier.

main(String[]) - Static method in class weka.classifiers.functions.supportVector.CheckKernel

Test method for this class

main(String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation

A test method for this class.

main(String[]) - Static method in class weka.classifiers.functions.VotedPerceptron

Main method.

main(String[]) - Static method in class weka.classifiers.lazy.IBk

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.lazy.KStar

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.lazy.LWL

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AdaBoostM1

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AdditiveRegression

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AttributeSelectedClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.Bagging

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.ClassificationViaRegression

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.CostSensitiveClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.CVParameterSelection

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.FilteredClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.IterativeClassifierOptimizer

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.LogitBoost

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.MultiClassClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.MultiClassClassifierUpdateable

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.MultiScheme

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.RandomCommittee

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.RandomizableFilteredClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.RandomSubSpace

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.RegressionByDiscretization

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.Stacking

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.Vote

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.misc.InputMappedClassifier

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.misc.SerializedClassifier

Runs the classifier with the given options

main(String[]) - Static method in class weka.classifiers.rules.DecisionTable

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.rules.JRip

Main method.

main(String[]) - Static method in class weka.classifiers.rules.M5Rules

Main method by which this class can be tested

main(String[]) - Static method in class weka.classifiers.rules.OneR

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.rules.PART

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.rules.ZeroR

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.trees.DecisionStump

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.trees.HoeffdingTree

main(String[]) - Static method in class weka.classifiers.trees.J48

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.trees.LMT

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.trees.M5P

Main method by which this class can be tested

main(String[]) - Static method in class weka.classifiers.trees.RandomForest

Main method for this class.

main(String[]) - Static method in class weka.classifiers.trees.RandomTree

Main method for this class.

main(String[]) - Static method in class weka.classifiers.trees.REPTree

Main method for this class.

main(String[]) - Static method in class weka.clusterers.Canopy

main(String[]) - Static method in class weka.clusterers.CheckClusterer

Test method for this class

main(String[]) - Static method in class weka.clusterers.ClusterEvaluation

Main method for testing this class.

main(String[]) - Static method in class weka.clusterers.Cobweb

Main method.

main(String[]) - Static method in class weka.clusterers.EM

Main method for testing this class.

main(String[]) - Static method in class weka.clusterers.FarthestFirst

Main method for testing this class.

main(String[]) - Static method in class weka.clusterers.FilteredClusterer

Main method for testing this class.

main(String[]) - Static method in class weka.clusterers.HierarchicalClusterer

main(String[]) - Static method in class weka.clusterers.MakeDensityBasedClusterer

Main method for testing this class.

main(String[]) - Static method in class weka.clusterers.SimpleKMeans

Main method for executing this class.

main(String[]) - Static method in class weka.core.AlgVector

Main method for testing this class, can take an ARFF file as first argument.

main(String[]) - Static method in class weka.core.AllJavadoc

Parses the given commandline parameters and generates the Javadoc.

main(String[]) - Static method in class weka.core.Attribute

Simple main method for testing this class.

main(String[]) - Static method in class weka.core.BinarySparseInstance

Main method for testing this class.

main(String[]) - Static method in class weka.core.Capabilities

loads the given dataset and prints the Capabilities necessary to process it.

main(String[]) - Static method in class weka.core.CheckGOE

Main method for using the CheckGOE.

main(String[]) - Static method in class weka.core.CheckOptionHandler

Main method for using the CheckOptionHandler.

main(String[]) - Static method in class weka.core.ClassCache

For testing only.

main(String[]) - Static method in class weka.core.ClassDiscovery

Possible calls: weka.core.ClassDiscovery <packages>
Prints all the packages in the current classpath weka.core.ClassDiscovery <classname> <packagename(s)>
Prints the classes it found.

main(String[]) - Static method in class weka.core.ContingencyTables

Main method for testing this class.

main(String[]) - Static method in class weka.core.converters.ArffLoader

Main method.

main(String[]) - Static method in class weka.core.converters.ArffSaver

Main method.

main(String[]) - Static method in class weka.core.converters.C45Loader

Main method for testing this class.

main(String[]) - Static method in class weka.core.converters.C45Saver

Main method.

main(String[]) - Static method in class weka.core.converters.ConverterUtils.DataSink

for testing only - takes a data file as input and a data file for the output.

main(String[]) - Static method in class weka.core.converters.ConverterUtils.DataSource

for testing only - takes a data file as input.

main(String[]) - Static method in class weka.core.converters.CSVLoader

Main method.

main(String[]) - Static method in class weka.core.converters.CSVSaver

Main method.

main(String[]) - Static method in class weka.core.converters.DatabaseLoader

Main method.

main(String[]) - Static method in class weka.core.converters.DatabaseSaver

Main method.

main(String[]) - Static method in class weka.core.converters.JSONLoader

Main method.

main(String[]) - Static method in class weka.core.converters.JSONSaver

Main method.

main(String[]) - Static method in class weka.core.converters.LibSVMLoader

Main method.

main(String[]) - Static method in class weka.core.converters.LibSVMSaver

Main method.

main(String[]) - Static method in class weka.core.converters.MatlabLoader

Main method.

main(String[]) - Static method in class weka.core.converters.MatlabSaver

Main method.

main(String[]) - Static method in class weka.core.converters.SerializedInstancesLoader

Main method.

main(String[]) - Static method in class weka.core.converters.SerializedInstancesSaver

Main method.

main(String[]) - Static method in class weka.core.converters.SVMLightLoader

Main method.

main(String[]) - Static method in class weka.core.converters.SVMLightSaver

Main method.

main(String[]) - Static method in class weka.core.converters.TextDirectoryLoader

Main method.

main(String[]) - Static method in class weka.core.converters.XRFFLoader

Main method.

main(String[]) - Static method in class weka.core.converters.XRFFSaver

Main method.

main(String[]) - Static method in class weka.core.Copyright

Only for testing

main(String[]) - Static method in class weka.core.DenseInstance

Main method for testing this class.

main(String[]) - Static method in class weka.core.Environment

Main method for testing this class.

main(String[]) - Static method in class weka.core.FindWithCapabilities

Executes the location of classes with parameters from the commandline.

main(String[]) - Static method in class weka.core.GlobalInfoJavadoc

Parses the given commandline parameters and generates the Javadoc.

main(String[]) - Static method in class weka.core.InstanceComparator

for testing only.

main(String[]) - Static method in class weka.core.Instances

Main method for this class.

main(String[]) - Static method in class weka.core.json.JSONInstances

For testing only.

main(String[]) - Static method in class weka.core.json.JSONNode

Only for testing.

main(String[]) - Static method in class weka.core.json.Parser

Runs the parser from commandline.

main(String[]) - Static method in class weka.core.ListOptions

runs the javadoc producer with the given commandline options

main(String[]) - Static method in class weka.core.mathematicalexpression.Parser

Runs the parser from commandline.

main(String[]) - Static method in class weka.core.matrix.DoubleVector

main(String[]) - Static method in class weka.core.matrix.IntVector

Tests the IntVector class

main(String[]) - Static method in class weka.core.Matrix

Deprecated. Main method for testing this class.

main(String[]) - Static method in class weka.core.matrix.Matrix

Main method for testing this class.

main(String[]) - Static method in class weka.core.Memory

prints only some statistics

main(String[]) - Static method in class weka.core.neighboursearch.CoverTree

Method for testing the class from command line.

main(String[]) - Static method in class weka.core.OptionHandlerJavadoc

Parses the given commandline parameters and generates the Javadoc.

main(String[]) - Static method in class weka.core.pmml.Constant

main(String[]) - Static method in class weka.core.pmml.PMMLFactory

main(String[]) - Static method in class weka.core.PropertyPath

for testing only

main(String[]) - Static method in class weka.core.Queue

Main method for testing this class.

main(String[]) - Static method in class weka.core.RandomVariates

Main method for testing this class.

main(String[]) - Static method in class weka.core.Range

Main method for testing this class.

main(String[]) - Static method in class weka.core.RepositoryIndexGenerator

Main method for running the RepositoryIndexGenerator

main(String[]) - Static method in class weka.core.RevisionUtils

For testing only.

main(String[]) - Static method in class weka.core.scripting.Groovy

If no arguments are given, it just prints the presence of the Groovy classes, otherwise it expects a Groovy filename to execute.

main(String[]) - Static method in class weka.core.scripting.Jython

If no arguments are given, it just prints the presence of the Jython classes, otherwise it expects a Jython filename to execute.

main(String[]) - Static method in class weka.core.SerializationHelper

Outputs information about a class on the commandline, takes class name as arguments.

main(String[]) - Static method in class weka.core.SingleIndex

Main method for testing this class.

main(String[]) - Static method in class weka.core.SparseInstance

Main method for testing this class.

main(String[]) - Static method in class weka.core.SpecialFunctions

Main method for testing this class.

main(String[]) - Static method in class weka.core.Statistics

Main method for testing this class.

main(String[]) - Static method in class weka.core.stemmers.IteratedLovinsStemmer

Runs the stemmer with the given options

main(String[]) - Static method in class weka.core.stemmers.LovinsStemmer

Runs the stemmer with the given options

main(String[]) - Static method in class weka.core.stemmers.NullStemmer

Runs the stemmer with the given options

main(String[]) - Static method in class weka.core.stemmers.SnowballStemmer

Runs the stemmer with the given options.

main(String[]) - Static method in class weka.core.Stopwords

Accepts the following parameter:

-i file
loads the stopwords from the given file

-o file
saves the stopwords to the given file

-p
outputs the current stopwords on stdout

Any additional parameters are interpreted as words to test as stopwords.

main(String[]) - Static method in class weka.core.SystemInfo

for printing the system info to stdout.

main(String[]) - Static method in class weka.core.TechnicalInformation

Prints some examples of technical informations if there are no commandline options given.

main(String[]) - Static method in class weka.core.TechnicalInformationHandlerJavadoc

Parses the given commandline parameters and generates the Javadoc.

main(String[]) - Static method in class weka.core.TestInstances

for running the class from commandline, prints the generated data to stdout

main(String[]) - Static method in class weka.core.tokenizers.AlphabeticTokenizer

Runs the tokenizer with the given options and strings to tokenize.

main(String[]) - Static method in class weka.core.tokenizers.NGramTokenizer

Runs the tokenizer with the given options and strings to tokenize.

main(String[]) - Static method in class weka.core.tokenizers.WordTokenizer

Runs the tokenizer with the given options and strings to tokenize.

main(String[]) - Static method in class weka.core.Trie

Only for testing (prints the built Trie).

main(String[]) - Static method in class weka.core.Utils

Main method for testing this class.

main(String[]) - Static method in class weka.core.Version

only for testing

main(String[]) - Static method in class weka.core.WekaPackageManager

Main method for using the package manager from the command line

main(String[]) - Static method in class weka.core.xml.SerialUIDChanger

exchanges an old UID for a new one.

main(String[]) - Static method in class weka.core.xml.XMLDocument

for testing only.

main(String[]) - Static method in class weka.core.xml.XMLInstances

takes an XML document as first argument and then outputs the Instances statistics

main(String[]) - Static method in class weka.core.xml.XMLOptions

for testing only.

main(String[]) - Static method in class weka.core.xml.XMLSerialization

for testing only.

main(String[]) - Static method in class weka.datagenerators.classifiers.classification.Agrawal

Main method for executing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.classification.BayesNet

Main method for executing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.classification.LED24

Main method for executing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.classification.RandomRBF

Main method for executing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.classification.RDG1

Main method for testing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.regression.Expression

Main method for testing this class.

main(String[]) - Static method in class weka.datagenerators.classifiers.regression.MexicanHat

Main method for testing this class.

main(String[]) - Static method in class weka.datagenerators.clusterers.BIRCHCluster

Main method for testing this class.

main(String[]) - Static method in class weka.datagenerators.clusterers.SubspaceCluster

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.CheckEstimator

Test method for this class

main(String[]) - Static method in class weka.estimators.DDConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.DiscreteEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.DKConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.DNConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.KDConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.KernelEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.KKConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.MahalanobisEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.MultivariateGaussianEstimator

main(String[]) - Static method in class weka.estimators.NDConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.NNConditionalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.NormalEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.PoissonEstimator

Main method for testing this class.

main(String[]) - Static method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Main method, used for testing this class.

main(String[]) - Static method in class weka.estimators.UnivariateKernelEstimator

Main method, used for testing this class.

main(String[]) - Static method in class weka.estimators.UnivariateNormalEstimator

Main method, used for testing this class.

main(String[]) - Static method in class weka.experiment.CrossValidationResultProducer

Quick test of timestamp

main(String[]) - Static method in class weka.experiment.Experiment

Configures/Runs the Experiment from the command line.

main(String[]) - Static method in class weka.experiment.InstanceQuery

Test the class from the command line.

main(String[]) - Static method in class weka.experiment.OutputZipper

Main method for testing this class

main(String[]) - Static method in class weka.experiment.PairedCorrectedTTester

Test the class from the command line.

main(String[]) - Static method in class weka.experiment.PairedStats

Tests the paired stats object from the command line.

main(String[]) - Static method in class weka.experiment.PairedTTester

Test the class from the command line.

main(String[]) - Static method in class weka.experiment.RemoteEngine

Main method.

main(String[]) - Static method in class weka.experiment.RemoteExperiment

Configures/Runs the Experiment from the command line.

main(String[]) - Static method in class weka.experiment.ResultMatrixCSV

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixGnuPlot

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixHTML

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixLatex

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixPlainText

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixSignificance

for testing only.

main(String[]) - Static method in class weka.experiment.Stats

Tests the paired stats object from the command line.

main(String[]) - Static method in class weka.experiment.xml.XMLExperiment

for testing only.

main(String[]) - Static method in class weka.filters.AllFilter

Main method for testing this class.

main(String[]) - Static method in class weka.filters.CheckSource

Executes the tests, use "-h" to list the commandline options.

main(String[]) - Static method in class weka.filters.Filter

Main method for testing this class.

main(String[]) - Static method in class weka.filters.MultiFilter

Main method for executing this class.

main(String[]) - Static method in class weka.filters.supervised.attribute.AddClassification

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.AttributeSelection

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.attribute.ClassOrder

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.attribute.Discretize

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.attribute.MergeNominalValues

runs the filter with the given arguments

main(String[]) - Static method in class weka.filters.supervised.attribute.NominalToBinary

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.attribute.PartitionMembership

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.instance.Resample

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.instance.SpreadSubsample

Main method for testing this class.

main(String[]) - Static method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Add

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddCluster

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddExpression

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddID

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddNoise

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddUserFields

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddValues

Main method for testing and running this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Center

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ClassAssigner

Main method for executing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ClusterMembership

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Copy

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Discretize

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.FirstOrder

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.InterquartileRange

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.KernelFilter

runs the filter with the given arguments

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MakeIndicator

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MathExpression

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

runs the filter with the given arguments

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeManyValues

Main method for executing this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeTwoValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToBinary

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToString

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Normalize

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericCleaner

Runs the filter from commandline, use "-h" to see all options.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToBinary

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToNominal

Runs the filter with the given parameters.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericTransform

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Obfuscate

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Main method for executing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PKIDiscretize

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PrincipalComponents

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RandomProjection

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RandomSubset

Runs the filter with the given parameters.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Remove

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveByName

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveType

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveUseless

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RenameAttribute

Main method for executing this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RenameNominalValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Reorder

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SortLabels

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Standardize

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToNominal

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToWordVector

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SwapValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Transpose

runs the filter with the given arguments

main(String[]) - Static method in class weka.filters.unsupervised.instance.NonSparseToSparse

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.Randomize

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicates

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveFolds

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassified

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemovePercentage

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveRange

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithValues

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.Resample

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.ReservoirSample

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.SparseToNonSparse

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.SubsetByExpression

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Runs the parser from commandline.

main(String[]) - Static method in class weka.gui.arffviewer.ArffViewer

shows the frame and it tries to load all the arff files that were provided as arguments.

main(String[]) - Static method in class weka.gui.AttributeListPanel

Tests the attribute list panel from the command line.

main(String[]) - Static method in class weka.gui.AttributeSelectionPanel

Tests the attribute selection panel from the command line.

main(String[]) - Static method in class weka.gui.AttributeSummaryPanel

Tests out the attribute summary panel from the command line.

main(String[]) - Static method in class weka.gui.AttributeVisualizationPanel

Main method to test this class from command line

main(String[]) - Static method in class weka.gui.beans.AttributeSummarizer

main(String[]) - Static method in class weka.gui.beans.CostBenefitAnalysis

main(String[]) - Static method in class weka.gui.beans.DataVisualizer

main(String[]) - Static method in class weka.gui.beans.EnvironmentField

Main method for testing this class

main(String[]) - Static method in class weka.gui.beans.FlowRunner

Main method for testing this class.

main(String[]) - Static method in class weka.gui.beans.KnowledgeFlow

Shows the splash screen, launches the application and then disposes the splash screen.

main(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp

Main method.

main(String[]) - Static method in class weka.gui.beans.Loader

main(String[]) - Static method in class weka.gui.beans.LogPanel

Main method to test this class.

main(String[]) - Static method in class weka.gui.beans.ModelPerformanceChart

main(String[]) - Static method in class weka.gui.beans.Saver

The main method for testing

main(String[]) - Static method in class weka.gui.beans.ScatterPlotMatrix

main(String[]) - Static method in class weka.gui.beans.SQLViewerPerspective

Main method for testing this class

main(String[]) - Static method in class weka.gui.beans.StripChart

Tests out the StripChart from the command line

main(String[]) - Static method in class weka.gui.beans.TextViewer

main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanel

Main method for testing this class

main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed

Main method for testing this class

main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Main method for testing this class

main(String[]) - Static method in class weka.gui.ConverterFileChooser

For testing the file chooser.

main(String[]) - Static method in class weka.gui.DatabaseConnectionDialog

for testing only

main(String[]) - Static method in class weka.gui.experiment.AlgorithmListPanel

Tests out the algorithm list panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.DatasetListPanel

Tests out the dataset list panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.DistributeExperimentPanel

Tests out the panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.Experimenter

Tests out the experiment environment.

main(String[]) - Static method in class weka.gui.experiment.ExperimenterDefaults

only for testing - prints the content of the props file.

main(String[]) - Static method in class weka.gui.experiment.GeneratorPropertyIteratorPanel

Tests out the panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.HostListPanel

Tests out the host list panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.OutputFormatDialog

for testing only.

main(String[]) - Static method in class weka.gui.experiment.ResultsPanel

Tests out the results panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.RunNumberPanel

Tests out the panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.RunPanel

Tests out the run panel from the command line.

main(String[]) - Static method in class weka.gui.experiment.SetupPanel

Tests out the experiment setup from the command line.

main(String[]) - Static method in class weka.gui.explorer.AssociationsPanel

Tests out the Associator panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.AttributeSelectionPanel

Tests out the attribute selection panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.ClassifierPanel

Tests out the classifier panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.ClustererPanel

Tests out the clusterer panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.Explorer

Tests out the explorer environment.

main(String[]) - Static method in class weka.gui.explorer.ExplorerDefaults

only for testing - prints the content of the props file.

main(String[]) - Static method in class weka.gui.explorer.PreprocessPanel

Tests out the instance-preprocessing panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.VisualizePanel

Tests out the visualize panel from the command line.

main(String[]) - Static method in class weka.gui.GenericArrayEditor

Tests out the array editor from the command line.

main(String[]) - Static method in class weka.gui.GenericObjectEditor

Tests out the Object editor from the command line.

main(String[]) - Static method in class weka.gui.GenericPropertiesCreator

for generating props file: no parameter: see default constructor 1 parameter (i.e., filename): see default constructor + setOutputFilename(String) 2 parameters (i.e, filenames): see constructor with String argument + setOutputFilename(String)

main(String[]) - Static method in class weka.gui.graphvisualizer.GraphVisualizer

Main method to load a text file with the description of a graph from the command line

main(String[]) - Static method in class weka.gui.GUIChooser

Tests out the GUIChooser environment.

main(String[]) - Static method in class weka.gui.HierarchyPropertyParser

Tests out the parser.

main(String[]) - Static method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer

Main method for testing this class.

main(String[]) - Static method in class weka.gui.InstancesSummaryPanel

Tests out the instance summary panel from the command line.

main(String[]) - Static method in class weka.gui.ListSelectorDialog

Tests out the list selector from the command line.

main(String[]) - Static method in class weka.gui.LogPanel

Tests out the log panel from the command line.

main(String[]) - Static method in class weka.gui.LogWindow

for testing only

main(String[]) - Static method in class weka.gui.LookAndFeel

prints all the available LnFs to stdout

Main - Class in weka.gui

Menu-based GUI for Weka, replacement for the GUIChooser.

Main() - Constructor for class weka.gui.Main

default constructor.

main(String[]) - Static method in class weka.gui.Main

starts the application.

main(String[]) - Static method in class weka.gui.PackageManager

main(String[]) - Static method in class weka.gui.PropertySelectorDialog

Tests out the property selector from the command line.

main(String[]) - Static method in class weka.gui.ResultHistoryPanel

Tests out the result history from the command line.

main(String[]) - Static method in class weka.gui.SaveBuffer

Main method for testing this class

main(String[]) - Static method in class weka.gui.scripting.GroovyPanel

Displays the panel in a frame.

main(String[]) - Static method in class weka.gui.scripting.GroovyScript

Runs the script from commandline.

main(String[]) - Static method in class weka.gui.scripting.JythonPanel

Displays the panel in a frame.

main(String[]) - Static method in class weka.gui.scripting.JythonScript

Runs the script from commandline.

main(String[]) - Static method in class weka.gui.SelectedTagEditor

Tests out the selectedtag editor from the command line.

main(String[]) - Static method in class weka.gui.SimpleCLI

Method to start up the simple cli.

main(String[]) - Static method in class weka.gui.SimpleCLIPanel

Displays the panel in a frame.

main(String[]) - Static method in class weka.gui.sql.SqlViewer

starts the SQL-Viewer interface.

main(String[]) - Static method in class weka.gui.sql.SqlViewerDialog

for testing only.

main(String[]) - Static method in class weka.gui.treevisualizer.TreeVisualizer

Main method for testing this class.

main(String[]) - Static method in class weka.gui.visualize.AttributePanel

Main method for testing this class.

main(String[]) - Static method in class weka.gui.visualize.BMPWriter

for testing only.

main(String[]) - Static method in class weka.gui.visualize.ClassPanel

Main method for testing this class.

main(String[]) - Static method in class weka.gui.visualize.JPEGWriter

for testing only.

main(String[]) - Static method in class weka.gui.visualize.LegendPanel

Main method for testing this class

main(String[]) - Static method in class weka.gui.visualize.MatrixPanel

Main method for testing this class

main(String[]) - Static method in class weka.gui.visualize.Plot2D

Main method for testing this class

main(String[]) - Static method in class weka.gui.visualize.PNGWriter

for testing only.

main(String[]) - Static method in class weka.gui.visualize.PostscriptWriter

for testing only

main(String[]) - Static method in class weka.gui.visualize.ThresholdVisualizePanel

Starts the ThresholdVisualizationPanel with parameters from the command line.

main(String[]) - Static method in class weka.gui.visualize.VisualizePanel

Main method for testing this class

main(String[]) - Static method in class weka.gui.WekaTaskMonitor

Main method for testing this class

main(String[]) - Static method in class weka.Run

Main method for this class.

Main.BackgroundDesktopPane - Class in weka.gui

DesktopPane with background image.

Main.BackgroundDesktopPane(String) - Constructor for class weka.gui.Main.BackgroundDesktopPane

intializes the desktop pane.

Main.ChildFrameMDI - Class in weka.gui

Specialized JInternalFrame class.

Main.ChildFrameMDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameMDI

constructs a new internal frame that knows about its parent.

Main.ChildFrameSDI - Class in weka.gui

Specialized JFrame class.

Main.ChildFrameSDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameSDI

constructs a new internal frame that knows about its parent.

MainMenuExtension - Interface in weka.gui

Classes implementing this interface will be displayed in the "Extensions" menu in the main GUI of Weka.

MAJOR - Static variable in class weka.core.Version

the major version

MAJORITY_VOTING_RULE - Static variable in class weka.classifiers.meta.Vote

combination rule: Majority Voting (only nominal classes)

makeADTree(int, ArrayList<Integer>, Instances) - Static method in class weka.classifiers.bayes.net.ADNode

create sub tree

makeADTree(Instances) - Static method in class weka.classifiers.bayes.net.ADNode

create AD tree from set of instances

makeBinaryTipText() - Method in class weka.filters.supervised.attribute.Discretize

Returns the tip text for this property

makeBinaryTipText() - Method in class weka.filters.unsupervised.attribute.Discretize

Returns the tip text for this property

makeCopies(Associator, int) - Static method in class weka.associations.AbstractAssociator

Creates copies of the current associator.

makeCopies(ASEvaluation, int) - Static method in class weka.attributeSelection.ASEvaluation

Creates copies of the current evaluator.

makeCopies(ASSearch, int) - Static method in class weka.attributeSelection.ASSearch

Creates copies of the current search scheme.

makeCopies(Classifier, int) - Static method in class weka.classifiers.AbstractClassifier

Creates a given number of deep copies of the given classifier using serialization.

makeCopies(Kernel, int) - Static method in class weka.classifiers.functions.supportVector.Kernel

Creates a given number of deep or shallow (if the kernel implements Copyable) copies of the given kernel using serialization.

makeCopies(Clusterer, int) - Static method in class weka.clusterers.AbstractClusterer

Creates copies of the current clusterer.

makeCopies(DensityBasedClusterer, int) - Static method in class weka.clusterers.AbstractDensityBasedClusterer

Creates copies of the current clusterer.

makeCopies(Estimator, int) - Static method in class weka.estimators.Estimator

Creates a given number of deep copies of the given estimator using serialization.

makeCopies(Filter, int) - Static method in class weka.filters.Filter

Creates a given number of deep copies of the given filter using serialization.

makeCopy(Associator) - Static method in class weka.associations.AbstractAssociator

Creates a deep copy of the given associator using serialization.

makeCopy(Classifier) - Static method in class weka.classifiers.AbstractClassifier

Creates a deep copy of the given classifier using serialization.

makeCopy(Kernel) - Static method in class weka.classifiers.functions.supportVector.Kernel

Creates a shallow copy of the kernel (if it implements Copyable) otherwise a deep copy using serialization.

makeCopy(Clusterer) - Static method in class weka.clusterers.AbstractClusterer

Creates a deep copy of the given clusterer using serialization.

makeCopy(Estimator) - Static method in class weka.estimators.Estimator

Creates a deep copy of the given estimator using serialization.

makeCopy(Filter) - Static method in class weka.filters.Filter

Creates a deep copy of the given filter using serialization.

makeCopy(Object) - Static method in class weka.gui.GenericArrayEditor

Makes a copy of an object using serialization.

makeCopy(Object) - Static method in class weka.gui.GenericObjectEditor

Makes a copy of an object using serialization.

makeData(DataGenerator, String[]) - Static method in class weka.datagenerators.DataGenerator

Calls the data generator.

MakeDecList - Class in weka.classifiers.rules.part

Class for handling a decision list.

MakeDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for unpruned dec list.

MakeDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for dec list pruned using C4.5 pruning.

MakeDecList(ModelSelection, int, int, int) - Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for dec list pruned using hold-out pruning.

MakeDensityBasedClusterer - Class in weka.clusterers

Class for wrapping a Clusterer to make it return a distribution and density.

MakeDensityBasedClusterer() - Constructor for class weka.clusterers.MakeDensityBasedClusterer

Default constructor.

MakeDensityBasedClusterer(Clusterer) - Constructor for class weka.clusterers.MakeDensityBasedClusterer

Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.

makeDistribution(double, int) - Static method in class weka.classifiers.evaluation.NominalPrediction

Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.

MakeIndicator - Class in weka.filters.unsupervised.attribute

A filter that creates a new dataset with a boolean attribute replacing a nominal attribute.

MakeIndicator() - Constructor for class weka.filters.unsupervised.attribute.MakeIndicator

Constructor

makeUniformDistribution(int) - Static method in class weka.classifiers.evaluation.NominalPrediction

Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.

makeVaryNode(int, ArrayList<Integer>, Instances) - Static method in class weka.classifiers.bayes.net.ADNode

create sub tree

makeWeighted(CostMatrix) - Method in class weka.classifiers.evaluation.ConfusionMatrix

Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.

ManhattanDistance - Class in weka.core

Implements the Manhattan distance (or Taxicab geometry).

ManhattanDistance() - Constructor for class weka.core.ManhattanDistance

Constructs an Manhattan Distance object, Instances must be still set.

ManhattanDistance(Instances) - Constructor for class weka.core.ManhattanDistance

Constructs an Manhattan Distance object and automatically initializes the ranges.

map(String, String) - Method in class weka.core.matrix.DoubleVector

Applies a method to the vector

mapClasses(int, int, int[][], int[], double[], double[], int) - Static method in class weka.clusterers.ClusterEvaluation

Finds the minimum error mapping of classes to clusters.

MappingInfo - Class in weka.core.pmml

Class that maintains the mapping between incoming data set structure and that of the mining schema.

MappingInfo(Instances, MiningSchema, Logger) - Constructor for class weka.core.pmml.MappingInfo

mapToMiningSchema(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Map mining schema to incoming instances.

MapValues - Class in weka.core.pmml.jaxbbindings

Java class for MapValues element declaration.

MapValues() - Constructor for class weka.core.pmml.jaxbbindings.MapValues

margin() - Method in class weka.classifiers.evaluation.NominalPrediction

Calculates the prediction margin.

MarginCalculator - Class in weka.classifiers.bayes.net

MarginCalculator() - Constructor for class weka.classifiers.bayes.net.MarginCalculator

MarginCalculator.JunctionTreeNode - Class in weka.classifiers.bayes.net

MarginCalculator.JunctionTreeSeparator - Class in weka.classifiers.bayes.net

MarginCurve - Class in weka.classifiers.evaluation

Generates points illustrating the prediction margin.

MarginCurve() - Constructor for class weka.classifiers.evaluation.MarginCurve

markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

maskKeyword(String) - Method in class weka.experiment.DatabaseUtils

If the given string is a keyword, then the mask character will be appended and returned.

MatCell - Class in weka.core.pmml.jaxbbindings

Java class for MatCell element declaration.

MatCell() - Constructor for class weka.core.pmml.jaxbbindings.MatCell

MATCH_PART_SEPARATOR - Static variable in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Separator for parts of the match specification

MATCH_RULE_SEPARATOR - Static variable in class weka.gui.beans.SubstringLabelerRules

Separator for match rules in the internal representation

Matchable - Interface in weka.core

Interface to something that can be matched with tree matching algorithms.

matchMissingValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the tip text for this property

matchRulesFromInternal(String, Instances, String, Logger, Environment) - Static method in class weka.gui.beans.SubstringLabelerRules

Get a list of match rules from an internally encoded match specification

matchRulesFromInternal(String, Instances, String, Logger, Environment) - Static method in class weka.gui.beans.SubstringReplacerRules

Get a list of match rules from an internally encoded match specification

MathematicalExpression - Class in weka.core

Class for evaluating a string adhering the following grammar:

MathematicalExpression() - Constructor for class weka.core.MathematicalExpression

MathExpression - Class in weka.filters.unsupervised.attribute

Modify numeric attributes according to a given expression

Valid options are:

MathExpression() - Constructor for class weka.filters.unsupervised.attribute.MathExpression

Constructor

Maths - Class in weka.core.matrix

Utility class.

Maths() - Constructor for class weka.core.matrix.Maths

MatlabLoader - Class in weka.core.converters

Reads a Matlab file containing a single matrix in ASCII format.

MatlabLoader() - Constructor for class weka.core.converters.MatlabLoader

MatlabSaver - Class in weka.core.converters

Writes Matlab ASCII files, in single or double precision format.

MatlabSaver() - Constructor for class weka.core.converters.MatlabSaver

Constructor.

matrix() - Method in class weka.classifiers.trees.j48.Distribution

Returns matrix with distribution of class values.

Matrix - Class in weka.core

Deprecated. Use weka.core.matrix.Matrix instead - only for backwards compatibility.

Matrix(int, int) - Constructor for class weka.core.Matrix

Deprecated. Constructs a matrix and initializes it with default values.

Matrix(double[][]) - Constructor for class weka.core.Matrix

Deprecated. Constructs a matrix using a given array.

Matrix(Reader) - Constructor for class weka.core.Matrix

Deprecated. Reads a matrix from a reader.

Matrix - Class in weka.core.matrix

Jama = Java Matrix class.

Matrix(int, int) - Constructor for class weka.core.matrix.Matrix

Construct an m-by-n matrix of zeros.

Matrix(int, int, double) - Constructor for class weka.core.matrix.Matrix

Construct an m-by-n constant matrix.

Matrix(double[][]) - Constructor for class weka.core.matrix.Matrix

Construct a matrix from a 2-D array.

Matrix(double[][], int, int) - Constructor for class weka.core.matrix.Matrix

Construct a matrix quickly without checking arguments.

Matrix(double[], int) - Constructor for class weka.core.matrix.Matrix

Construct a matrix from a one-dimensional packed array

Matrix(Reader) - Constructor for class weka.core.matrix.Matrix

Reads a matrix from a reader.

Matrix - Class in weka.core.pmml.jaxbbindings

Java class for Matrix element declaration.

Matrix() - Constructor for class weka.core.pmml.jaxbbindings.Matrix

MATRIX_ON_DEMAND - Static variable in class weka.classifiers.meta.CostSensitiveClassifier

load cost matrix on demand

MATRIX_SUPPLIED - Static variable in class weka.classifiers.meta.CostSensitiveClassifier

use explicit cost matrix

MatrixPanel - Class in weka.gui.visualize

This panel displays a plot matrix of the user selected attributes of a given data set.

MatrixPanel() - Constructor for class weka.gui.visualize.MatrixPanel

Constructor

matrixToString(double[][]) - Static method in class weka.attributeSelection.PrincipalComponents

Return a matrix as a String

matthewsCorrelationCoefficient(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class

matthewsCorrelationCoefficient(int) - Method in class weka.classifiers.Evaluation

Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class

max() - Method in class weka.core.matrix.DoubleVector

Returns the maximum value of all elements

MAX - Static variable in class weka.core.neighboursearch.KDTree

The index of MAX value in attributes' range array.

MAX - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Index of max value in an array of attributes' range.

max - Variable in class weka.experiment.Stats

The maximum value seen, or Double.NaN if no values seen

MAX_DIGITS - Static variable in class weka.core.converters.SVMLightSaver

the number of digits after the decimal point.

MAX_HISTORY_COUNT - Static variable in class weka.gui.GenericObjectEditorHistory

the maximum entries in the history.

MAX_HISTORY_LENGTH - Static variable in class weka.gui.GenericObjectEditorHistory

the maximum length of a caption in the history.

MAX_LINE_LENGTH - Static variable in class weka.gui.GenericObjectEditorHistory

the menu max line length.

MAX_ROWS - Static variable in class weka.gui.sql.QueryPanel

the name for the max rows in the history.

MAX_RULE - Static variable in class weka.classifiers.meta.Vote

combination rule: Maximum Probability

MAX_SHAPES - Static variable in class weka.gui.visualize.Plot2D

MAX_SLEEP_TIME - Static variable in class weka.core.Memory

MAX_TABS - Static variable in class weka.gui.scripting.SyntaxDocument

the maximum number of tabs.

maxBag() - Method in class weka.classifiers.trees.j48.Distribution

Returns index of bag containing maximum number of instances.

maxBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic

Returns the tip text for this property

maxCardinalityTipText() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

maxClass() - Method in class weka.classifiers.trees.j48.Distribution

Returns class with highest frequency over all bags.

maxClass(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns class with highest frequency for given bag.

maxCountTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns the tip text for this property

maxDecimalPlacesTipText() - Method in class weka.core.converters.ArffSaver

Returns the tip text for this property.

maxDecimalPlacesTipText() - Method in class weka.core.converters.CSVSaver

Returns the tip text for this property.

maxDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

maxDepthTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

maxDepthTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

maxDepthTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

maxImpurity() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the impurity of this split

maxImpurity() - Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the impurity of this split

maxImpurity() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the impurity of this split

maximumAttributeNamesTipText() - Method in class weka.attributeSelection.PrincipalComponents

Returns the tip text for this property

maximumAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns the tip text for this property.

maximumAttributesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Returns the tip text for this property.

maximumNumberOfClustersTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

maximumVariancePercentageAllowedTipText() - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns the tip text for this property

maxIndex(double[]) - Static method in class weka.core.Utils

Returns index of maximum element in a given array of doubles.

maxIndex(int[]) - Static method in class weka.core.Utils

Returns index of maximum element in a given array of integers.

maxInstancesInLeafTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the tip text for this property.

maxInstInLeafTipText() - Method in class weka.core.neighboursearch.KDTree

Tip text for this property.

maxInstNumTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

maxInstNumTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns the tip text for this property

maxIterationsTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

maxIterationsTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property.

maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the tip text for this property

maxItsTipText() - Method in class weka.classifiers.functions.Logistic

Returns the tip text for this property

maxKTipText() - Method in class weka.classifiers.functions.VotedPerceptron

Returns the tip text for this property

maxNrOfParentsTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

maxNumberOfItemsTipText() - Method in class weka.associations.FPGrowth

Tip text for this property suitable for displaying in the GUI.

maxNumCandidateCanopiesToHoldInMemory() - Method in class weka.clusterers.Canopy

Returns the tip text for this property.

maxParentSetSize(int) - Method in class weka.classifiers.bayes.net.ParentSet

reserve memory for parent set

maxRadiusTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

maxRangeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns the tip text for this property

maxRelativeLeafRadiusTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Returns the tip text for this property.

maxRuleSizeTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

maxSubsequenceLengthTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the tip text for this property

maxThresholdTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

MAYBE_SUPPORT - Static variable in class weka.gui.GenericObjectEditor.GOETreeNode

color for "maybe support".

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.Filter

Default implementation returns false.

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.MultiFilter

RemoveWithValues may return false from input() (thus not making an instance available immediately) even after the first batch has been completed due to matching a value that the user wants to remove.

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

RemoveWithValues may return false from input() (thus not making an instance available immediately) even after the first batch has been completed due to matching a value that the user wants to remove.

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.unsupervised.instance.SubsetByExpression

SubsetByExpression may return false from input() (thus not making an instance available immediately) even after the first batch has been completed if the user has opted to apply the filter to instances after the first batch (rather than just passing them through).

MDL - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable

mean(double[]) - Static method in class weka.core.Utils

Computes the mean for an array of doubles.

mean - Variable in class weka.experiment.Stats

The mean of values at the last calculateDerived() call

meanAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the mean absolute error.

meanAbsoluteError() - Method in class weka.classifiers.Evaluation

Returns the mean absolute error.

meanOrMode(int) - Method in class weka.core.Instances

Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.

meanOrMode(Attribute) - Method in class weka.core.Instances

Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.

meanPrecTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

meanPriorAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the mean absolute error of the prior.

meanPriorAbsoluteError() - Method in class weka.classifiers.Evaluation

Returns the mean absolute error of the prior.

meanSquaredTipText() - Method in class weka.classifiers.lazy.IBk

Returns the tip text for this property.

meanStddevTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns the tip text for this property

meanWidthTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

measureAICScore() - Method in class weka.classifiers.bayes.BayesNet

measureAttributesUsed() - Method in class weka.classifiers.functions.SimpleLogistic

Returns the fraction of all attributes in the data that are used in the logistic model (in percent).

measureBayesScore() - Method in class weka.classifiers.bayes.BayesNet

measureBDeuScore() - Method in class weka.classifiers.bayes.BayesNet

measureDivergence() - Method in class weka.classifiers.bayes.BayesNet

measureEntropyScore() - Method in class weka.classifiers.bayes.BayesNet

measureExtraArcs() - Method in class weka.classifiers.bayes.BayesNet

measureMaxDepth() - Method in class weka.core.neighboursearch.BallTree

Returns the depth of the tree.

measureMaxDepth() - Method in class weka.core.neighboursearch.CoverTree

Returns the depth of the tree.

measureMaxDepth() - Method in class weka.core.neighboursearch.KDTree

Returns the depth of the tree.

measureMDLScore() - Method in class weka.classifiers.bayes.BayesNet

measureMissingArcs() - Method in class weka.classifiers.bayes.BayesNet

measureNumAttributesSelected() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- number of attributes selected

measureNumIterations() - Method in class weka.classifiers.meta.AdditiveRegression

return the number of iterations (base classifiers) completed

measureNumLeaves() - Method in class weka.classifiers.trees.J48

Returns the number of leaves

measureNumLeaves() - Method in class weka.classifiers.trees.LMT

Returns the number of leaves in the tree

measureNumLeaves() - Method in class weka.core.neighboursearch.BallTree

Returns the number of leaves.

measureNumLeaves() - Method in class weka.core.neighboursearch.CoverTree

Returns the number of leaves.

measureNumLeaves() - Method in class weka.core.neighboursearch.KDTree

Returns the number of leaves.

measureNumRules() - Method in class weka.classifiers.rules.DecisionTable

Returns the number of rules

measureNumRules() - Method in class weka.classifiers.rules.PART

Return the number of rules.

measureNumRules() - Method in class weka.classifiers.trees.J48

Returns the number of rules (same as number of leaves)

measureNumRules() - Method in class weka.classifiers.trees.m5.M5Base

return the number of rules

measureOutOfBagError() - Method in class weka.classifiers.meta.Bagging

Gets the out of bag error that was calculated as the classifier was built.

measureOutOfBagError() - Method in class weka.classifiers.trees.RandomForest

Gets the out of bag error that was calculated as the classifier was built.

measurePerformanceTipText() - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns the tip text for this property.

measureReversedArcs() - Method in class weka.classifiers.bayes.BayesNet

measureSelectionTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- time taken (milliseconds) to select the attributes

measureTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- time taken (milliseconds) to select attributes and build the classifier

measureTreeSize() - Method in class weka.classifiers.trees.J48

Returns the size of the tree

measureTreeSize() - Method in class weka.classifiers.trees.LMT

Returns the size of the tree

measureTreeSize() - Method in class weka.core.neighboursearch.BallTree

Returns the size of the tree.

measureTreeSize() - Method in class weka.core.neighboursearch.CoverTree

Returns the size of the tree.

measureTreeSize() - Method in class weka.core.neighboursearch.KDTree

Returns the size of the tree.

MEDIAN_RULE - Static variable in class weka.classifiers.meta.Vote

combination rule: Median Probability (only numeric class)

MedianDistanceFromArbitraryPoint - Class in weka.core.neighboursearch.balltrees

Class that splits a BallNode of a ball tree using Uhlmann's described method.

For information see:

Jeffrey K.

MedianDistanceFromArbitraryPoint() - Constructor for class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Constructor.

MedianDistanceFromArbitraryPoint(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Constructor.

MedianOfWidestDimension - Class in weka.core.neighboursearch.balltrees

Class that splits a BallNode of a ball tree based on the median value of the widest dimension of the points in the ball.

MedianOfWidestDimension() - Constructor for class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Constructor.

MedianOfWidestDimension(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Constructor.

MedianOfWidestDimension - Class in weka.core.neighboursearch.kdtrees

The class that splits a KDTree node based on the median value of a dimension in which the node's points have the widest spread.

For more information see also:

Jerome H.

MedianOfWidestDimension() - Constructor for class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Memory - Class in weka.core

A little helper class for Memory management.

Memory() - Constructor for class weka.core.Memory

initializes the memory management without GUI support

Memory(boolean) - Constructor for class weka.core.Memory

initializes the memory management

memoryIsLow() - Method in class weka.core.Memory

Checks to see if memory is running low.

MemoryUsagePanel - Class in weka.gui

A panel for displaying the memory usage.

MemoryUsagePanel() - Constructor for class weka.gui.MemoryUsagePanel

default constructor.

mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.AprioriItemSet

Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.

mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.ItemSet

Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.

mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.LabeledItemSet

Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.

MergeInfrequentNominalValues - Class in weka.filters.unsupervised.attribute

Merges all values of the specified nominal attribute that are sufficiently infrequent.

MergeInfrequentNominalValues() - Constructor for class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

mergeInstance(Instance) - Method in class weka.core.BinarySparseInstance

Merges this instance with the given instance and returns the result.

mergeInstance(Instance) - Method in class weka.core.DenseInstance

Merges this instance with the given instance and returns the result.

mergeInstance(Instance) - Method in interface weka.core.Instance

Merges this instance with the given instance and returns the result.

mergeInstance(Instance) - Method in class weka.core.SparseInstance

Merges this instance with the given instance and returns the result.

mergeInstances(Instances, Instances) - Static method in class weka.core.Instances

Merges two sets of Instances together.

MergeManyValues - Class in weka.filters.unsupervised.attribute

Merges many values of a nominal attribute into one value.

MergeManyValues() - Constructor for class weka.filters.unsupervised.attribute.MergeManyValues

MergeNominalValues - Class in weka.filters.supervised.attribute

Merges values of all nominal attributes among the specified attributes, excluding the class attribute, using the CHAID method, but without considering to re-split merged subsets.

MergeNominalValues() - Constructor for class weka.filters.supervised.attribute.MergeNominalValues

MergeTwoValues - Class in weka.filters.unsupervised.attribute

Merges two values of a nominal attribute into one value.

MergeTwoValues() - Constructor for class weka.filters.unsupervised.attribute.MergeTwoValues

mergeValueRangeTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Returns the tip text for this property.

MetaBean - Class in weka.gui.beans

A meta bean that encapsulates several other regular beans, useful for grouping large KnowledgeFlows.

MetaBean() - Constructor for class weka.gui.beans.MetaBean

metaClassifierTipText() - Method in class weka.classifiers.meta.Stacking

Returns the tip text for this property

METHOD_1_AGAINST_1 - Static variable in class weka.classifiers.meta.MultiClassClassifier

1-against-1

METHOD_1_AGAINST_ALL - Static variable in class weka.classifiers.meta.MultiClassClassifier

1-against-all

METHOD_ERROR_EXHAUSTIVE - Static variable in class weka.classifiers.meta.MultiClassClassifier

exhaustive correction code

METHOD_ERROR_RANDOM - Static variable in class weka.classifiers.meta.MultiClassClassifier

random correction code

MethodHandler - Class in weka.core.xml

This class handles relationships between display names of properties (or classes) and Methods that are associated with them.

MethodHandler() - Constructor for class weka.core.xml.MethodHandler

initializes the handler

methodNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns the tip text for this property

methodTipText() - Method in class weka.classifiers.meta.MultiClassClassifier

metricIsMaximisable(String) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper

Returns true if the named metric is maximisable

metricString() - Method in class weka.associations.Apriori

Returns the metric string for the chosen metric type

metricString() - Method in interface weka.associations.CARuleMiner

Gets name of the scoring metric used for car mining

metricTypeTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

metricTypeTipText() - Method in class weka.associations.FPGrowth

Tip text for this property suitable for displaying in the GUI.

MexicanHat - Class in weka.datagenerators.classifiers.regression

A data generator for the simple 'Mexian Hat' function:
y = sin|x| / |x|
In addition to this simple function, the amplitude can be changed and gaussian noise can be added.

MexicanHat() - Constructor for class weka.datagenerators.classifiers.regression.MexicanHat

initializes the generator

MiddleOutConstructor - Class in weka.core.neighboursearch.balltrees

The class that builds a BallTree middle out.

For more information see also:

Andrew W.

MiddleOutConstructor() - Constructor for class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Creates a new instance of MiddleOutConstructor.

MidPointOfWidestDimension - Class in weka.core.neighboursearch.kdtrees

The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.

For more information see also:

Andrew Moore (1991).

MidPointOfWidestDimension() - Constructor for class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

MIN - Static variable in class weka.core.neighboursearch.KDTree

The index of MIN value in attributes' range array.

MIN - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Index of min value in an array of attributes' range.

min - Variable in class weka.experiment.Stats

The minimum value seen, or Double.NaN if no values seen

MIN_RULE - Static variable in class weka.classifiers.meta.Vote

combination rule: Minimum Probability

minBoxRelWidthTipText() - Method in class weka.core.neighboursearch.KDTree

Tip text for this property.

minBucketSizeTipText() - Method in class weka.classifiers.rules.OneR

Returns the tip text for this property

minDataDLIfDeleted(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats

Compute the minimal data description length of the ruleset if the rule in the given position is deleted.
The min_data_DL_if_deleted = data_DL_if_deleted - potential

minDataDLIfExists(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats

Compute the minimal data description length of the ruleset if the rule in the given position is NOT deleted.
The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential

minDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

mineCARs(Instances) - Method in class weka.associations.Apriori

Method that mines all class association rules with minimum support and with a minimum confidence.

mineCARs(Instances) - Method in interface weka.associations.CARuleMiner

Method for mining class association rules.

minimalTipText() - Method in class weka.classifiers.functions.LinearRegression

Returns the tip text for this property.

minimizeAbsoluteErrorTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns the tip text for this property

minimizeExpectedCostTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier

minimizeWindows() - Method in class weka.gui.Main

minimizes all windows.

minimumBucketSizeTipText() - Method in class weka.attributeSelection.OneRAttributeEval

Returns a string for this option suitable for display in the gui as a tip text

minimumCanopyDensityTipText() - Method in class weka.clusterers.Canopy

Returns the tip text for this property.

minimumFractionOfWeightInfoGainTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

minimumFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Returns the tip text for this property

minIndex(int[]) - Static method in class weka.core.Utils

Returns index of minimum element in a given array of integers.

minIndex(double[]) - Static method in class weka.core.Utils

Returns index of minimum element in a given array of doubles.

MiningBuildTask - Class in weka.core.pmml.jaxbbindings

Java class for MiningBuildTask element declaration.

MiningBuildTask() - Constructor for class weka.core.pmml.jaxbbindings.MiningBuildTask

MiningField - Class in weka.core.pmml.jaxbbindings

Java class for MiningField element declaration.

MiningField() - Constructor for class weka.core.pmml.jaxbbindings.MiningField

MiningField(String, FIELDUSAGETYPE) - Constructor for class weka.core.pmml.jaxbbindings.MiningField

MiningField(String, FIELDUSAGETYPE, MISSINGVALUETREATMENTMETHOD, String) - Constructor for class weka.core.pmml.jaxbbindings.MiningField

MiningFieldMetaInfo - Class in weka.core.pmml

Class encapsulating information about a MiningField.

MiningFieldMetaInfo(Element) - Constructor for class weka.core.pmml.MiningFieldMetaInfo

Constructs a new MiningFieldMetaInfo object.

MININGFUNCTION - Enum in weka.core.pmml.jaxbbindings

Java class for MINING-FUNCTION.

MiningModel - Class in weka.core.pmml.jaxbbindings

Java class for MiningModel element declaration.

MiningModel() - Constructor for class weka.core.pmml.jaxbbindings.MiningModel

MiningSchema - Class in weka.core.pmml.jaxbbindings

Java class for MiningSchema element declaration.

MiningSchema() - Constructor for class weka.core.pmml.jaxbbindings.MiningSchema

MiningSchema - Class in weka.core.pmml

This class encapsulates the mining schema from a PMML xml file.

MiningSchema(Element, Instances, TransformationDictionary) - Constructor for class weka.core.pmml.MiningSchema

Constructor for MiningSchema.

minInstNumTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

minInstNumTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Returns the tip text for this property

Minkowski - Class in weka.core.pmml.jaxbbindings

Java class for minkowski element declaration.

Minkowski() - Constructor for class weka.core.pmml.jaxbbindings.Minkowski

MinkowskiDistance - Class in weka.core

Implementing Minkowski distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.

MinkowskiDistance() - Constructor for class weka.core.MinkowskiDistance

Constructs an Minkowski Distance object, Instances must be still set.

MinkowskiDistance(Instances) - Constructor for class weka.core.MinkowskiDistance

Constructs an Minkowski Distance object and automatically initializes the ranges.

minLogLikelihoodImprovementCVTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

minLogLikelihoodImprovementIteratingTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

minMetricTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

minMetricTipText() - Method in class weka.associations.FPGrowth

Returns the tip text for this property

minNoTipText() - Method in class weka.classifiers.rules.JRip

Returns the tip text for this property

minNumInstancesTipText() - Method in class weka.classifiers.trees.LMT

Returns the tip text for this property

minNumInstancesTipText() - Method in class weka.classifiers.trees.m5.M5Base

Returns the tip text for this property

minNumObjTipText() - Method in class weka.classifiers.rules.PART

Returns the tip text for this property

minNumObjTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

minNumTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

minNumTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

MINOR - Static variable in class weka.core.Version

the minor version

minProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper

used/reused to hold the smallest transformation probability

minRadiusTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

minRangeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns the tip text for this property

minRuleSizeTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

minsAndMaxs(Instances, double[][], int) - Method in class weka.classifiers.trees.j48.C45Split

Returns the minsAndMaxs of the index.th subset.

minStdDevTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

minStdDevTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns the tip text for this property

minTermFreqTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

minThresholdTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Returns the tip text for this property

MINUS - Static variable in interface weka.core.mathematicalexpression.sym

minus(double) - Method in class weka.core.matrix.DoubleVector

Subtracts a value

minus(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Subtracts another DoubleVector element by element

minus(Matrix) - Method in class weka.core.matrix.Matrix

C = A - B

MINUS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

minusEquals(double) - Method in class weka.core.matrix.DoubleVector

Subtracts a value in place

minusEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Subtracts another DoubleVector element by element in place

minusEquals(Matrix) - Method in class weka.core.matrix.Matrix

A = A - B

minVariancePropTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

minVariancePropTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

minWordFrequencyTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

minWordFrequencyTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

MISSING_SHAPE - Static variable in class weka.gui.visualize.Plot2D

MISSING_VALUE - Static variable in interface weka.classifiers.evaluation.Prediction

Constant representing a missing value.

MISSING_VALUE - Static variable in class weka.core.json.JSONInstances

the missing value indicator.

missingArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader

Count nr of arcs missing from other network compared to current network Note that an arc is not 'missing' if it is reversed.

missingCount - Variable in class weka.core.AttributeStats

The number of missing values

missingMergeTipText() - Method in class weka.attributeSelection.GainRatioAttributeEval

Returns the tip text for this property

missingMergeTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns the tip text for this property

missingMergeTipText() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns the tip text for this property

missingModeTipText() - Method in class weka.classifiers.lazy.KStar

Returns the tip text for this property

missingSeparateTipText() - Method in class weka.attributeSelection.CfsSubsetEval

Returns the tip text for this property

missingValue() - Static method in class weka.core.Utils

Returns the value used to code a missing value.

MISSINGVALUESTRATEGY - Enum in weka.core.pmml.jaxbbindings

Java class for MISSING-VALUE-STRATEGY.

missingValueTipText() - Method in class weka.core.converters.CSVLoader

Returns the tip text for this property.

missingValueTipText() - Method in class weka.core.converters.CSVSaver

Returns the tip text for this property.

MISSINGVALUETREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for MISSING-VALUE-TREATMENT-METHOD.

MissingValueWeights - Class in weka.core.pmml.jaxbbindings

Java class for MissingValueWeights element declaration.

MissingValueWeights() - Constructor for class weka.core.pmml.jaxbbindings.MissingValueWeights

MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClassifierPanel

The filename extension that should be used for model files.

MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClustererPanel

The filename extension that should be used for model files

modelBuilt() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

flag to indicate whether the model was built yet

modelDistributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode

Returns the class probabilities for an instance according to the logistic model at the node.

ModelExplanation - Class in weka.core.pmml.jaxbbindings

Java class for ModelExplanation element declaration.

ModelExplanation() - Constructor for class weka.core.pmml.jaxbbindings.ModelExplanation

modelFileTipText() - Method in class weka.classifiers.misc.SerializedClassifier

Returns the tip text for this property

ModelLiftGraph - Class in weka.core.pmml.jaxbbindings

Java class for ModelLiftGraph element declaration.

ModelLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.ModelLiftGraph

modelPathTipText() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the tip text for this property

ModelPerformanceChart - Class in weka.gui.beans

Bean that can be used for displaying threshold curves (e.g.

ModelPerformanceChart() - Constructor for class weka.gui.beans.ModelPerformanceChart

ModelPerformanceChartBeanInfo - Class in weka.gui.beans

Bean info class for the model performance chart

ModelPerformanceChartBeanInfo() - Constructor for class weka.gui.beans.ModelPerformanceChartBeanInfo

ModelPerformanceChartCustomizer - Class in weka.gui.beans

GUI customizer for model performance chart.

ModelPerformanceChartCustomizer() - Constructor for class weka.gui.beans.ModelPerformanceChartCustomizer

Constructor

ModelSelection - Class in weka.classifiers.trees.j48

Abstract class for model selection criteria.

ModelSelection() - Constructor for class weka.classifiers.trees.j48.ModelSelection

ModelStats - Class in weka.core.pmml.jaxbbindings

Java class for ModelStats element declaration.

ModelStats() - Constructor for class weka.core.pmml.jaxbbindings.ModelStats

modelsToString() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns a string describing the logistic regression function at the node.

ModelVerification - Class in weka.core.pmml.jaxbbindings

Java class for ModelVerification element declaration.

ModelVerification() - Constructor for class weka.core.pmml.jaxbbindings.ModelVerification

modifyHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns the tip text for this property

modifyHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the tip text for this property

momentumTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

moralize(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator

moralize DAG and calculate adjacency matrix representation for a Bayes Network, effecively converting the directed acyclic graph to an undirected graph.

mostRecentVersionWithRespectToConstraint(PackageConstraint) - Static method in class weka.core.WekaPackageManager

Find the most recent version of the package encapsulated in the supplied PackageConstraint argument that satisfies the constraint

mouseClicked(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when a mouse button has been pressed and released on a component

mouseClicked(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseDragged(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Performs intermediate updates to what the user wishes to do.

mouseEntered(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when the mouse enters a component.

mouseEntered(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseExited(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when the mouse exits a component

mouseExited(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseMoved(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mousePressed(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when a mouse button has been pressed on a component

mousePressed(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Determines what action the user wants to perform.

mouseReleased(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when a mouse button has been released on a component.

mouseReleased(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer

Performs the final stages of what the user wants to perform.

move(File, File) - Static method in class weka.gui.scripting.ScriptUtils

Moves the file/directory (recursively).

MOVE_DOWN - Static variable in class weka.gui.JListHelper

moves items down

MOVE_UP - Static variable in class weka.gui.JListHelper

moves items up

moveBottom(JList) - Static method in class weka.gui.JListHelper

moves the selected items to the end

moveDown(JList) - Static method in class weka.gui.JListHelper

moves the selected item down by 1

moveTop(JList) - Static method in class weka.gui.JListHelper

moves the selected items to the top

moveUp(JList) - Static method in class weka.gui.JListHelper

moves the selected items up by 1

MultiClassClassifier - Class in weka.classifiers.meta

A metaclassifier for handling multi-class datasets with 2-class classifiers.

MultiClassClassifier() - Constructor for class weka.classifiers.meta.MultiClassClassifier

Constructor.

MultiClassClassifierUpdateable - Class in weka.classifiers.meta

A metaclassifier for handling multi-class datasets with 2-class classifiers.

MultiClassClassifierUpdateable() - Constructor for class weka.classifiers.meta.MultiClassClassifierUpdateable

Constructor

MultiFilter - Class in weka.filters

Applies several filters successively.

MultiFilter() - Constructor for class weka.filters.MultiFilter

MultiInstanceCapabilitiesHandler - Interface in weka.core

Multi-Instance classifiers can specify an additional Capabilities object for the data in the relational attribute, since the format of multi-instance data is fixed to "bag/NOMINAL,data/RELATIONAL,class".

MultilayerPerceptron - Class in weka.classifiers.functions

A Classifier that uses backpropagation to classify instances.
This network can be built by hand, created by an algorithm or both.

MultilayerPerceptron() - Constructor for class weka.classifiers.functions.MultilayerPerceptron

The constructor.

MultiNomialBMAEstimator - Class in weka.classifiers.bayes.net.estimate

Multinomial BMA Estimator.

MultiNomialBMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

MultipleClassifiersCombiner - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.

MultipleClassifiersCombiner() - Constructor for class weka.classifiers.MultipleClassifiersCombiner

MULTIPLEMODELMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for MULTIPLE-MODEL-METHOD.

multiply(Matrix) - Method in class weka.core.Matrix

Deprecated. Returns the multiplication of two matrices

multiResultsetFull(int, int) - Method in class weka.experiment.PairedTTester

Creates a comparison table where a base resultset is compared to the other resultsets.

multiResultsetFull(int, int) - Method in interface weka.experiment.Tester

Creates a comparison table where a base resultset is compared to the other resultsets.

multiResultsetRanking(int) - Method in class weka.experiment.PairedTTester

returns a ranking of the resultsets

multiResultsetRanking(int) - Method in interface weka.experiment.Tester

multiResultsetSummary(int) - Method in class weka.experiment.PairedTTester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

multiResultsetSummary(int) - Method in interface weka.experiment.Tester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

multiResultsetWins(int, int[][]) - Method in class weka.experiment.PairedTTester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

multiResultsetWins(int, int[][]) - Method in interface weka.experiment.Tester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

MultiScheme - Class in weka.classifiers.meta

Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.

MultiScheme() - Constructor for class weka.classifiers.meta.MultiScheme

MultivariateEstimator - Interface in weka.estimators

Interface to Multivariate Distribution Estimation

MultivariateGaussianEstimator - Class in weka.estimators

Implementation of Multivariate Distribution Estimation using Normal Distribution.

MultivariateGaussianEstimator() - Constructor for class weka.estimators.MultivariateGaussianEstimator

MultivariateGaussianEstimator(double[], double[][]) - Constructor for class weka.estimators.MultivariateGaussianEstimator

MultivariateStat - Class in weka.core.pmml.jaxbbindings

Java class for MultivariateStat element declaration.

MultivariateStat() - Constructor for class weka.core.pmml.jaxbbindings.MultivariateStat

MultivariateStats - Class in weka.core.pmml.jaxbbindings

Java class for MultivariateStats element declaration.

MultivariateStats() - Constructor for class weka.core.pmml.jaxbbindings.MultivariateStats

N

NaiveBayes - Class in weka.classifiers.bayes

Class for a Naive Bayes classifier using estimator classes.

NaiveBayes() - Constructor for class weka.classifiers.bayes.NaiveBayes

NaiveBayes - Class in weka.classifiers.bayes.net.search.fixed

The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.

NaiveBayes() - Constructor for class weka.classifiers.bayes.net.search.fixed.NaiveBayes

NaiveBayesModel - Class in weka.core.pmml.jaxbbindings

Java class for NaiveBayesModel element declaration.

NaiveBayesModel() - Constructor for class weka.core.pmml.jaxbbindings.NaiveBayesModel

NaiveBayesMultinomial - Class in weka.classifiers.bayes

Class for building and using a multinomial Naive Bayes classifier.

NaiveBayesMultinomial() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomial

NaiveBayesMultinomialText - Class in weka.classifiers.bayes

Multinomial naive bayes for text data.

NaiveBayesMultinomialText() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomialText

NaiveBayesMultinomialUpdateable - Class in weka.classifiers.bayes

Class for building and using a multinomial Naive Bayes classifier.

NaiveBayesMultinomialUpdateable() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable

naiveBayesPredictionThresholdTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

NaiveBayesUpdateable - Class in weka.classifiers.bayes

Class for a Naive Bayes classifier using estimator classes.

NaiveBayesUpdateable() - Constructor for class weka.classifiers.bayes.NaiveBayesUpdateable

name() - Method in class weka.core.Attribute

Returns the attribute's name.

NAME - Static variable in class weka.core.json.JSONInstances

the name attribute.

name() - Method in class weka.core.Option

Returns the option's name.

NAME_CLASSFIRST - Static variable in class weka.experiment.xml.XMLExperiment

the name of the classFirst property

NAME_PROPERTYNODE_PARENTCLASS - Static variable in class weka.experiment.xml.XMLExperiment

PropertyNode member

NAME_PROPERTYNODE_PROPERTY - Static variable in class weka.experiment.xml.XMLExperiment

PropertyNode member

NAME_PROPERTYNODE_VALUE - Static variable in class weka.experiment.xml.XMLExperiment

PropertyNode member

NamedColor - Class in weka.gui.treevisualizer

This class contains a color name and the rgb values of that color

NamedColor(String, int, int, int) - Constructor for class weka.gui.treevisualizer.NamedColor

nameTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression

Returns the tip text for this property

NBNode - Class in weka.classifiers.trees.ht

Implements a LearningNode that uses a naive Bayes model

NBNode(Instances, double) - Constructor for class weka.classifiers.trees.ht.NBNode

Construct a new NBNode

NBNodeAdaptive - Class in weka.classifiers.trees.ht

Implements a LearningNode that chooses between using majority class or naive Bayes for prediction

NBNodeAdaptive(Instances, double) - Constructor for class weka.classifiers.trees.ht.NBNodeAdaptive

Constructor

NBTreeClassifierTree - Class in weka.classifiers.trees.j48

Class for handling a naive bayes tree structure used for classification.

NBTreeClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.NBTreeClassifierTree

NBTreeModelSelection - Class in weka.classifiers.trees.j48

Class for selecting a NB tree split.

NBTreeModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.NBTreeModelSelection

Initializes the split selection method with the given parameters.

NBTreeNoSplit - Class in weka.classifiers.trees.j48

Class implementing a "no-split"-split (leaf node) for naive bayes trees.

NBTreeNoSplit() - Constructor for class weka.classifiers.trees.j48.NBTreeNoSplit

NBTreeSplit - Class in weka.classifiers.trees.j48

Class implementing a NBTree split on an attribute.

NBTreeSplit(int, int, double) - Constructor for class weka.classifiers.trees.j48.NBTreeSplit

Initializes the split model.

NDConditionalEstimator - Class in weka.estimators

Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate normal estimators for each discrete conditioning value).

NDConditionalEstimator(int, double) - Constructor for class weka.estimators.NDConditionalEstimator

Constructor

NearestNeighborModel - Class in weka.core.pmml.jaxbbindings

Java class for NearestNeighborModel element declaration.

NearestNeighborModel() - Constructor for class weka.core.pmml.jaxbbindings.NearestNeighborModel

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.BallTree

Returns the nearest instance in the current neighbourhood to the supplied instance.

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.CoverTree

Returns the NN instance of a given target instance, from among the previously supplied training instances.

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.KDTree

Returns the nearest neighbour of the supplied target instance.

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch

Returns the nearest instance in the current neighbourhood to the supplied instance.

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Returns the nearest instance in the current neighbourhood to the supplied instance.

NearestNeighbourSearch - Class in weka.core.neighboursearch

Abstract class for nearest neighbour search.

NearestNeighbourSearch() - Constructor for class weka.core.neighboursearch.NearestNeighbourSearch

Constructor.

NearestNeighbourSearch(Instances) - Constructor for class weka.core.neighboursearch.NearestNeighbourSearch

Constructor.

nearestNeighbourSearchAlgorithmTipText() - Method in class weka.classifiers.lazy.IBk

Returns the tip text for this property.

nearestNeighbourSearchAlgorithmTipText() - Method in class weka.classifiers.lazy.LWL

Returns the tip text for this property.

needExponentialFormat(double) - Method in class weka.core.matrix.FlexibleDecimalFormat

needsUID(String) - Static method in class weka.core.SerializationHelper

checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.

needsUID(Class<?>) - Static method in class weka.core.SerializationHelper

checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.

NeuralConnection - Class in weka.classifiers.functions.neural

Abstract unit in a NeuralNetwork.

NeuralConnection(String) - Constructor for class weka.classifiers.functions.neural.NeuralConnection

Constructs The unit with the basic connection information prepared for use.

NeuralInput - Class in weka.core.pmml.jaxbbindings

Java class for NeuralInput element declaration.

NeuralInput() - Constructor for class weka.core.pmml.jaxbbindings.NeuralInput

NeuralInputs - Class in weka.core.pmml.jaxbbindings

Java class for NeuralInputs element declaration.

NeuralInputs() - Constructor for class weka.core.pmml.jaxbbindings.NeuralInputs

NeuralLayer - Class in weka.core.pmml.jaxbbindings

Java class for NeuralLayer element declaration.

NeuralLayer() - Constructor for class weka.core.pmml.jaxbbindings.NeuralLayer

NeuralMethod - Interface in weka.classifiers.functions.neural

This is an interface used to create classes that can be used by the neuralnode to perform all it's computations.

NeuralNetwork - Class in weka.classifiers.pmml.consumer

Class implementing import of PMML Neural Network model.

NeuralNetwork(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.NeuralNetwork

NeuralNetwork - Class in weka.core.pmml.jaxbbindings

Java class for NeuralNetwork element declaration.

NeuralNetwork() - Constructor for class weka.core.pmml.jaxbbindings.NeuralNetwork

NeuralNode - Class in weka.classifiers.functions.neural

This class is used to represent a node in the neuralnet.

NeuralNode(String, Random, NeuralMethod) - Constructor for class weka.classifiers.functions.neural.NeuralNode

NeuralOutput - Class in weka.core.pmml.jaxbbindings

Java class for NeuralOutput element declaration.

NeuralOutput() - Constructor for class weka.core.pmml.jaxbbindings.NeuralOutput

NeuralOutputs - Class in weka.core.pmml.jaxbbindings

Java class for NeuralOutputs element declaration.

NeuralOutputs() - Constructor for class weka.core.pmml.jaxbbindings.NeuralOutputs

Neuron - Class in weka.core.pmml.jaxbbindings

Java class for Neuron element declaration.

Neuron() - Constructor for class weka.core.pmml.jaxbbindings.Neuron

NEW_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent

newClassLoader() - Static method in class weka.core.scripting.Groovy

initializes and returns a Groovy Interpreter.

newClock() - Static method in class weka.core.Debug

returns a new instance of a clock

newDataFormat(DataSetEvent) - Method in class weka.gui.beans.ClassAssignerCustomizer

newDataFormat(DataSetEvent) - Method in interface weka.gui.beans.DataFormatListener

Recieve a DataSetEvent that encapsulates a new data format.

newDocument(String, String) - Method in class weka.core.xml.XMLDocument

creates a new Document with the given information.

newEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit

Computes entropy of distribution after splitting.

Newick - Static variable in interface weka.core.Drawable

newInstance(File, Class<?>) - Static method in class weka.core.scripting.Groovy

loads the module and returns a new instance of it as instance of the provided Java class template.

newInstance(File, Class<?>) - Static method in class weka.core.scripting.Jython

loads the module and returns a new instance of it as instance of the provided Java class template.

newInstance(File, Class<?>, File[]) - Static method in class weka.core.scripting.Jython

loads the module and returns a new instance of it as instance of the provided Java class template.

newInterpreter() - Static method in class weka.core.scripting.Jython

initializes and returns a Python Interpreter

newLog(String, int, int) - Static method in class weka.core.Debug

returns a new Log instance

newNominalRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR

Create a rule branching on this nominal attribute.

newNumericRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR

Create a rule branching on this numeric attribute

newRandom() - Static method in class weka.core.Debug

returns a default debug random object, with no particular seed and debugging enabled.

newRandom(int) - Static method in class weka.core.Debug

returns a debug random object with the specified seed and debugging enabled.

newRule(Attribute, Instances) - Method in class weka.classifiers.rules.OneR

Create a rule branching on this attribute.

newThread(String[]) - Method in class weka.gui.scripting.GroovyScript

Returns a new thread to execute.

newThread(String[]) - Method in class weka.gui.scripting.JythonScript

Returns a new thread to execute.

newThread(String[]) - Method in class weka.gui.scripting.Script

Returns a new thread to execute.

newTimestamp() - Static method in class weka.core.Debug

returns a default timestamp for the current date/time

next() - Method in interface weka.classifiers.IterativeClassifier

Performs one iteration.

next - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry

next table entry (separate chaining)

next() - Method in class weka.classifiers.meta.LogitBoost

Perform another iteration of boosting.

next() - Method in class weka.core.Trie.TrieIterator

Returns the next element in the iteration.

next_token() - Method in class weka.core.json.Scanner

Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.

next_token() - Method in class weka.core.mathematicalexpression.Scanner

Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.

next_token() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner

Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.

nextBoolean() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.

nextBytes(byte[]) - Method in class weka.core.Debug.Random

Generates random bytes and places them into a user-supplied byte array.

nextDouble() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.

nextElement(Instances) - Method in class weka.core.converters.ConverterUtils.DataSource

returns the next element and sets the specified dataset, null if none available.

nextElement() - Method in class weka.core.tokenizers.AlphabeticTokenizer

returns the next element

nextElement() - Method in class weka.core.tokenizers.NGramTokenizer

Returns N-grams and also (N-1)-grams and ....

nextElement() - Method in class weka.core.tokenizers.Tokenizer

Returns the next element of this enumeration if this enumeration object has at least one more element to provide.

nextElement() - Method in class weka.core.tokenizers.WordTokenizer

Returns the next element of this enumeration if this enumeration object has at least one more element to provide.

nextElement() - Method in class weka.core.WekaEnumeration

Returns the next element.

nextErlang(int) - Method in class weka.core.RandomVariates

Generate a value of a variate following standard Erlang distribution.

nextExponential() - Method in class weka.core.RandomVariates

Generate a value of a variate following standard exponential distribution using simple inverse method.

nextFloat() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.

nextGamma(double) - Method in class weka.core.RandomVariates

Generate a value of a variate following standard Gamma distribution with shape parameter a.

nextGaussian() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.

nextInt() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.

nextInt(int) - Method in class weka.core.Debug.Random

Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.

nextIteration() - Method in class weka.experiment.Experiment

Carries out the next iteration of the experiment.

nextIteration() - Method in class weka.experiment.RemoteExperiment

Overides the one in Experiment

nextLong() - Method in class weka.core.Debug.Random

Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.

NGramMaxSizeTipText() - Method in class weka.core.tokenizers.NGramTokenizer

Returns the tip text for this property.

NGramMinSizeTipText() - Method in class weka.core.tokenizers.NGramTokenizer

Returns the tip text for this property.

NGramTokenizer - Class in weka.core.tokenizers

Splits a string into an n-gram with min and max grams.

NGramTokenizer() - Constructor for class weka.core.tokenizers.NGramTokenizer

NNConditionalEstimator - Class in weka.estimators

Conditional probability estimator for a numeric domain conditional upon a numeric domain (using Mahalanobis distance).

NNConditionalEstimator() - Constructor for class weka.estimators.NNConditionalEstimator

NNNORMALIZATIONMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for NN-NORMALIZATION-METHOD.

NO_CLASS - Static variable in class weka.associations.CheckAssociator

a "dummy" class type

NO_CLASS - Static variable in class weka.core.TestInstances

can be used to avoid generating a class attribute

NO_CLASS - Static variable in class weka.gui.SetInstancesPanel

the text denoting "no class" in the class combobox.

NO_COMMAND - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

NO_SUPPORT - Static variable in class weka.gui.GenericObjectEditor.GOETreeNode

color for "no support".

Node - Class in weka.core.pmml.jaxbbindings

Java class for Node element declaration.

Node() - Constructor for class weka.core.pmml.jaxbbindings.Node

Node - Class in weka.gui.treevisualizer

This class records all the data about a particular node for displaying.

Node(String, String, int, int, Color, String) - Constructor for class weka.gui.treevisualizer.Node

This will setup all the values of the node except for its top and center.

NodePlace - Interface in weka.gui.treevisualizer

This is an interface for classes that wish to take a node structure and arrange them

nodeSplitterTipText() - Method in class weka.core.neighboursearch.KDTree

Returns the tip text for this property.

nodeToString() - Method in class weka.classifiers.trees.m5.RuleNode

Returns a description of this node (debugging purposes)

nodeType - Variable in class weka.gui.graphvisualizer.GraphNode

Type of node.

noHeaderRowPresentTipText() - Method in class weka.core.converters.CSVLoader

Returns the tip text for this property.

noHeaderRowTipText() - Method in class weka.core.converters.CSVSaver

Returns the tip text for this property.

noisePercentTipText() - Method in class weka.datagenerators.classifiers.classification.LED24

Returns the tip text for this property

noiseRateTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns the tip text for this property

noiseRateTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

noiseRateTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns the tip text for this property

noiseTipText() - Method in class weka.classifiers.functions.GaussianProcesses

Returns the tip text for this property

noiseVarianceTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Returns the tip text for this property

NOMINAL - Static variable in class weka.core.Attribute

Constant set for nominal attributes.

nominalAttributesTipText() - Method in class weka.core.converters.CSVLoader

Returns the tip text for this property.

nominalColsTipText() - Method in class weka.datagenerators.ClusterGenerator

Returns the tip text for this property

NominalConditionalSufficientStats - Class in weka.classifiers.trees.ht

Maintains sufficient stats for the distribution of a nominal attribute

NominalConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.NominalConditionalSufficientStats

nominalCounts - Variable in class weka.core.AttributeStats

Counts of each nominal value

nominalIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the tip text for this property

NominalItem - Class in weka.associations

Class that encapsulates a nominal item.

NominalItem(Attribute, int) - Constructor for class weka.associations.NominalItem

Constructs a new NominalItem.

nominalLabelSpecsTipText() - Method in class weka.core.converters.CSVLoader

Returns the tip text for this property.

nominalLabelsTipText() - Method in class weka.filters.unsupervised.attribute.Add

Returns the tip text for this property.

NominalPrediction - Class in weka.classifiers.evaluation

Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.

NominalPrediction(double, double[]) - Constructor for class weka.classifiers.evaluation.NominalPrediction

Creates the NominalPrediction object with a default weight of 1.0.

NominalPrediction(double, double[], double) - Constructor for class weka.classifiers.evaluation.NominalPrediction

Creates the NominalPrediction object.

nominalStringReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Tip text for this property suitable for displaying in the GUI.

NominalToBinary - Class in weka.filters.supervised.attribute

Converts all nominal attributes into binary numeric attributes.

NominalToBinary() - Constructor for class weka.filters.supervised.attribute.NominalToBinary

NominalToBinary - Class in weka.filters.unsupervised.attribute

Converts all nominal attributes into binary numeric attributes.

NominalToBinary() - Constructor for class weka.filters.unsupervised.attribute.NominalToBinary

Constructor - initialises the filter

nominalToBinaryFilterTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

NominalToString - Class in weka.filters.unsupervised.attribute

Converts a nominal attribute (i.e.

NominalToString() - Constructor for class weka.filters.unsupervised.attribute.NominalToString

nominalWeights - Variable in class weka.core.AttributeStats

Weight mass for each nominal value

NON_NUMERIC - Static variable in class weka.filters.unsupervised.attribute.InterquartileRange

indicator for non-numeric attributes

NONE - Static variable in interface weka.core.converters.Loader

The retrieval modes

NONE - Static variable in interface weka.core.converters.Saver

The retrieval modes

NONE - Static variable in class weka.gui.visualize.VisualizePanelEvent

No longer used

nonEmptyCanopySetIntersection(long[], long[]) - Static method in class weka.clusterers.Canopy

Tests if two sets of canopies have a non-empty intersection

NonSparseToSparse - Class in weka.filters.unsupervised.instance

An instance filter that converts all incoming instances into sparse format.

NonSparseToSparse() - Constructor for class weka.filters.unsupervised.instance.NonSparseToSparse

noPruningTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

noReplacementTipText() - Method in class weka.filters.supervised.instance.Resample

Returns the tip text for this property.

noReplacementTipText() - Method in class weka.filters.unsupervised.instance.Resample

Returns the tip text for this property

norm() - Method in class weka.core.AlgVector

Returns the norm of the vector

norm1() - Method in class weka.core.matrix.DoubleVector

Returns the L1-norm of the vector

norm1() - Method in class weka.core.matrix.Matrix

One norm

norm2() - Method in class weka.core.matrix.DoubleVector

Returns the L2-norm of the vector

norm2() - Method in class weka.core.matrix.Matrix

Two norm

norm2() - Method in class weka.core.matrix.SingularValueDecomposition

Two norm

NORM_EXPECTED_COST_NAME - Static variable in class weka.classifiers.evaluation.CostCurve

attribute name: Normalized Expected Cost

NORMAL - Static variable in interface weka.gui.graphvisualizer.GraphConstants

NORMAL node - node actually contained in graphs description

normalDistribution - Static variable in class weka.core.matrix.Maths

Distribution type: noraml

NormalEstimator - Class in weka.estimators

Simple probability estimator that places a single normal distribution over the observed values.

NormalEstimator(double) - Constructor for class weka.estimators.NormalEstimator

Constructor that takes a precision argument.

normalInverse(double) - Static method in class weka.core.Statistics

Returns the value, x, for which the area under the Normal (Gaussian) probability density function (integrated from minus infinity to x) is equal to the argument y (assumes mean is zero, variance is one).

NormalizableDistance - Class in weka.core

Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.

NormalizableDistance() - Constructor for class weka.core.NormalizableDistance

Invalidates the distance function, Instances must be still set.

NormalizableDistance(Instances) - Constructor for class weka.core.NormalizableDistance

Initializes the distance function and automatically initializes the ranges.

normalize() - Method in class weka.classifiers.CostMatrix

Normalizes the matrix so that the diagonal contains zeros.

normalize(double[]) - Static method in class weka.core.Utils

Normalizes the doubles in the array by their sum.

normalize(double[], double) - Static method in class weka.core.Utils

Normalizes the doubles in the array using the given value.

Normalize - Class in weka.filters.unsupervised.attribute

Normalizes all numeric values in the given dataset (apart from the class attribute, if set).

Normalize() - Constructor for class weka.filters.unsupervised.attribute.Normalize

normalizeAttributesTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

normalizeDimWidthsTipText() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Returns the tip text for this property.

normalizedKernel(char[], char[]) - Method in class weka.classifiers.functions.supportVector.StringKernel

evaluates the normalized kernel between s and t.

normalizeDocLengthTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

normalizeDocLengthTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

normalizeDocLengthTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

NormalizedPolyKernel - Class in weka.classifiers.functions.supportVector

The normalized polynomial kernel.
K(x,y) = <x,y>/sqrt(<x,x><y,y>) where <x,y> = PolyKernel(x,y)

Valid options are:

NormalizedPolyKernel() - Constructor for class weka.classifiers.functions.supportVector.NormalizedPolyKernel

default constructor - does nothing

NormalizedPolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.NormalizedPolyKernel

Creates a new NormalizedPolyKernel instance.

normalizeNodeWidthTipText() - Method in class weka.core.neighboursearch.KDTree

Tip text for this property.

normalizeNumericClassTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

normalProbability(double) - Static method in class weka.core.Statistics

Returns the area under the Normal (Gaussian) probability density function, integrated from minus infinity to x (assumes mean is zero, variance is one).

NormContinuous - Class in weka.core.pmml.jaxbbindings

Java class for NormContinuous element declaration.

NormContinuous() - Constructor for class weka.core.pmml.jaxbbindings.NormContinuous

NormContinuous - Class in weka.core.pmml

Class encapsulating a NormContinuous Expression.

NormContinuous(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.NormContinuous

NormDiscrete - Class in weka.core.pmml.jaxbbindings

Java class for NormDiscrete element declaration.

NormDiscrete() - Constructor for class weka.core.pmml.jaxbbindings.NormDiscrete

NormDiscrete(String, String) - Constructor for class weka.core.pmml.jaxbbindings.NormDiscrete

NormDiscrete - Class in weka.core.pmml

Class encapsulating a NormDiscrete Expression.

NormDiscrete(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.NormDiscrete

Constructor.

normF() - Method in class weka.core.matrix.Matrix

Frobenius norm

normInf() - Method in class weka.core.matrix.Matrix

Infinity norm

normTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

normTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

normVector() - Method in class weka.core.AlgVector

Norms this vector to length 1.0

NORTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual

noSizeDeterminationTipText() - Method in class weka.experiment.ClassifierSplitEvaluator

Returns the tip text for this property

noSizeDeterminationTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns the tip text for this property

noSizeDeterminationTipText() - Method in class weka.experiment.RegressionSplitEvaluator

Returns the tip text for this property

NoSplit - Class in weka.classifiers.trees.j48

Class implementing a "no-split"-split.

NoSplit(Distribution) - Constructor for class weka.classifiers.trees.j48.NoSplit

Creates "no-split"-split for given distribution.

NoSupportForMissingValuesException - Exception in weka.core

Exception that is raised by an object that is unable to process data with missing values.

NoSupportForMissingValuesException() - Constructor for exception weka.core.NoSupportForMissingValuesException

Creates a new NoSupportForMissingValuesException with no message.

NoSupportForMissingValuesException(String) - Constructor for exception weka.core.NoSupportForMissingValuesException

Creates a new NoSupportForMissingValuesException.

NOT - Static variable in interface weka.core.mathematicalexpression.sym

NOT - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

NOT_DRAWABLE - Static variable in interface weka.core.Drawable

notCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule

Get the instances not covered by this rule

Note - Class in weka.gui.beans

Simple bean for displaying a textual note on the layout.

Note() - Constructor for class weka.gui.beans.Note

Constructor

NoteBeanInfo - Class in weka.gui.beans

Bean info class for the Note bean.

NoteBeanInfo() - Constructor for class weka.gui.beans.NoteBeanInfo

NoteCustomizer - Class in weka.gui.beans

Customizer for the note component.

NoteCustomizer() - Constructor for class weka.gui.beans.NoteCustomizer

Constructs a new note customizer

notifyCapabilitiesFilterListener(Capabilities) - Method in class weka.gui.explorer.Explorer

notifies all the listeners of a change

notifyListener() - Method in class weka.gui.arffviewer.ArffPanel

notfies all listener of the change

notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffSortedTableModel

notfies all listener of the change of the model

notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTableModel

notfies all listener of the change of the model

NOTRUECHILDSTRATEGY - Enum in weka.core.pmml.jaxbbindings

Java class for NO-TRUE-CHILD-STRATEGY.

nrOfGoodOperationsTipText() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

nrOfLookAheadStepsTipText() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Null - Class in weka.classifiers.evaluation.output.prediction

Suppresses all output.

Null() - Constructor for class weka.classifiers.evaluation.output.prediction.Null

NULL - Static variable in interface weka.core.json.sym

NullStemmer - Class in weka.core.stemmers

A dummy stemmer that performs no stemming at all.

NullStemmer() - Constructor for class weka.core.stemmers.NullStemmer

NUM_RAND_COLS - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

numAllConditions(Instances) - Static method in class weka.classifiers.rules.RuleStats

Compute the number of all possible conditions that could appear in a rule of a given data.

numArcsTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Returns the tip text for this property

numArguments() - Method in class weka.core.Option

Returns the option's number of arguments.

numAttributes() - Method in class weka.core.DenseInstance

Returns the number of attributes.

numAttributes() - Method in interface weka.core.Instance

Returns the number of attributes.

numAttributes() - Method in class weka.core.Instances

Returns the number of attributes.

numAttributes() - Method in class weka.core.SparseInstance

Returns the number of attributes.

numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet

Returns the tip text for this property

numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns the tip text for this property

numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

numAttributesTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster

Returns the tip text for this property

numAttributesTipText() - Method in class weka.datagenerators.ClusterGenerator

Returns the tip text for this property

numAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns the tip text for this property.

numBags() - Method in class weka.classifiers.trees.j48.Distribution

Returns number of bags.

NUMBER - Static variable in interface weka.core.mathematicalexpression.sym

NUMBER - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

numberAttributesSelected() - Method in class weka.attributeSelection.AttributeSelection

Return the number of attributes selected from the most recent run of attribute selection

numberOfAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the tip text for this property

numberOfClusters() - Method in class weka.clusterers.AbstractClusterer

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.Canopy

numberOfClusters() - Method in interface weka.clusterers.Clusterer

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.Cobweb

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.EM

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.FarthestFirst

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.HierarchicalClusterer

numberOfClusters() - Method in class weka.clusterers.MakeDensityBasedClusterer

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.SimpleKMeans

Returns the number of clusters.

numberOfClusters() - Method in class weka.clusterers.SingleClustererEnhancer

Returns the number of clusters.

NumberOfClustersRequestable - Interface in weka.clusterers

Interface to a clusterer that can generate a requested number of clusters

numberOfLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode

Get the number of linear models in the tree

numBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns the tip text for this property

numBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic

Returns the tip text for this property

numBoostingIterationsTipText() - Method in class weka.classifiers.trees.LMT

Returns the tip text for this property

numCacheHits() - Method in class weka.classifiers.functions.supportVector.CachedKernel

Returns the number of cache hits on dot products.

numCacheHits() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns the number of dot product cache hits.

numCacheHits() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns the number of dot product cache hits.

numCacheHits() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the number of dot product cache hits.

numCentroidsTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns the tip text for this property

numChildred() - Method in class weka.classifiers.trees.ht.SplitNode

Number of child nodes

numChildren() - Method in class weka.gui.HierarchyPropertyParser

The number of the children nodes.

numClassAttributeValues() - Method in class weka.classifiers.functions.SMO

numClasses() - Method in class weka.classifiers.trees.j48.Distribution

Returns number of classes.

numClasses() - Method in class weka.core.AbstractInstance

Returns the number of class labels.

numClasses() - Method in interface weka.core.Instance

Returns the number of class labels.

numClasses() - Method in class weka.core.Instances

Returns the number of class labels.

numClassesTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Returns the tip text for this property

numClassesTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

numClustersTipText() - Method in class weka.clusterers.Canopy

Returns the tip text for this property.

numClustersTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

numClustersTipText() - Method in class weka.clusterers.FarthestFirst

Returns the tip text for this property

numClustersTipText() - Method in class weka.clusterers.HierarchicalClusterer

numClustersTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property.

numClustersTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

numColumns() - Method in class weka.classifiers.CostMatrix

Same as size

numColumns() - Method in class weka.core.Matrix

Deprecated. Returns the number of columns in the matrix.

numCorrect() - Method in class weka.classifiers.trees.j48.Distribution

Returns perClass(maxClass()).

numCorrect(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns perClassPerBag(index,maxClass(index)).

numCyclesTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

numDecimalsTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the tip text for this property.

numDistinctValues(int) - Method in class weka.core.Instances

Returns the number of distinct values of a given attribute.

numDistinctValues(Attribute) - Method in class weka.core.Instances

Returns the number of distinct values of a given attribute.

numElements() - Method in class weka.classifiers.functions.supportVector.SMOset

Returns the number of elements in the set.

numElements() - Method in class weka.classifiers.meta.Bagging

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.meta.FilteredClassifier

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.meta.RandomCommittee

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.trees.J48

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.trees.RandomForest

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.trees.RandomTree

Returns the number of elements in the partition.

numElements() - Method in class weka.classifiers.trees.REPTree

Returns the number of elements in the partition.

numElements() - Method in class weka.core.AlgVector

Returns the number of elements in the vector.

numElements() - Method in interface weka.core.PartitionGenerator

Returns the number of elements in the partition.

numEntriesInClassDistribution() - Method in class weka.classifiers.trees.ht.HNode

The size of the class distribution

NUMERIC - Static variable in class weka.core.Attribute

Constant set for numeric attributes.

NumericCleaner - Class in weka.filters.unsupervised.attribute

A filter that 'cleanses' the numeric data from values that are too small, too big or very close to a certain value (e.g., 0) and sets these values to a pre-defined default.

NumericCleaner() - Constructor for class weka.filters.unsupervised.attribute.NumericCleaner

NumericInfo - Class in weka.core.pmml.jaxbbindings

Java class for NumericInfo element declaration.

NumericInfo() - Constructor for class weka.core.pmml.jaxbbindings.NumericInfo

NumericItem - Class in weka.associations

Class that encapsulates a numeric item.

NumericItem(Attribute, double, NumericItem.Comparison) - Constructor for class weka.associations.NumericItem

Constructs a new NumericItem

NumericItem.Comparison - Enum in weka.associations

NumericPrediction - Class in weka.classifiers.evaluation

Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.

NumericPrediction(double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction

Creates the NumericPrediction object with a default weight of 1.0.

NumericPrediction(double, double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction

Creates the NumericPrediction object.

NumericPrediction(double, double, double, double[][]) - Constructor for class weka.classifiers.evaluation.NumericPrediction

Creates the NumericPrediction object.

NumericPredictor - Class in weka.core.pmml.jaxbbindings

Java class for NumericPredictor element declaration.

NumericPredictor() - Constructor for class weka.core.pmml.jaxbbindings.NumericPredictor

NumericPredictor(String, BigInteger, double) - Constructor for class weka.core.pmml.jaxbbindings.NumericPredictor

numericReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Tip text for this property suitable for displaying in the GUI.

numericStats - Variable in class weka.core.AttributeStats

Stats on numeric value distributions

numericTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator

NumericToBinary - Class in weka.filters.unsupervised.attribute

Converts all numeric attributes into binary attributes (apart from the class attribute, if set): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.

NumericToBinary() - Constructor for class weka.filters.unsupervised.attribute.NumericToBinary

NumericToNominal - Class in weka.filters.unsupervised.attribute

A filter for turning numeric attributes into nominal ones.

NumericToNominal() - Constructor for class weka.filters.unsupervised.attribute.NumericToNominal

NumericTransform - Class in weka.filters.unsupervised.attribute

Transforms numeric attributes using a given transformation method.

NumericTransform() - Constructor for class weka.filters.unsupervised.attribute.NumericTransform

Default constructor -- sets the default transform method to java.lang.Math.abs().

numEvals() - Method in class weka.classifiers.functions.supportVector.CachedKernel

Returns the number of time Eval has been called.

numEvals() - Method in class weka.classifiers.functions.supportVector.Kernel

Returns the number of kernel evaluation performed.

numEvals() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Returns the number of kernel evaluation performed.

numEvals() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the number of kernel evaluation performed.

numExamplesTipText() - Method in class weka.datagenerators.ClassificationGenerator

Returns the tip text for this property

numExamplesTipText() - Method in class weka.datagenerators.RegressionGenerator

Returns the tip text for this property

numExecutionSlotsTipText() - Method in class weka.attributeSelection.GreedyStepwise

numExecutionSlotsTipText() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Returns the tip text for this property

numExecutionSlotsTipText() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Returns the tip text for this property

numExecutionSlotsTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

numExecutionSlotsTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

numExecutionSlotsTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property

numFalseNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate number of false negatives with respect to a particular class.

numFalseNegatives(int) - Method in class weka.classifiers.Evaluation

Calculate number of false negatives with respect to a particular class.

numFalsePositives(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate number of false positives with respect to a particular class.

numFalsePositives(int) - Method in class weka.classifiers.Evaluation

Calculate number of false positives with respect to a particular class.

numFeaturesTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.functions.SMO

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.meta.CVParameterSelection

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.meta.MultiScheme

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.meta.Stacking

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.rules.PART

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

numFoldsTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

numFoldsTipText() - Method in class weka.clusterers.EM

Returns the tip text for this property

numFoldsTipText() - Method in class weka.experiment.CrossValidationResultProducer

Returns the tip text for this property

numFoldsTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns the tip text for this property

numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns the tip text for this property

numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the tip text for this property

numIncorrect() - Method in class weka.classifiers.trees.j48.Distribution

Returns total-numCorrect().

numIncorrect(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns perBag(index)-numCorrect(index).

numInstances() - Method in class weka.classifiers.evaluation.Evaluation

Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).

numInstances() - Method in class weka.classifiers.Evaluation

Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).

numInstances() - Method in class weka.core.Instances

Returns the number of instances in the dataset.

numInstances() - Method in class weka.core.neighboursearch.balltrees.BallNode

Returns the number of instances in the hyper-spherical region of this node.

numInstances() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode

Returns the number of Instances in the rectangular region defined by this node.

numIrrelevantTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

numIterationsTipText() - Method in class weka.classifiers.functions.VotedPerceptron

Returns the tip text for this property

numIterationsTipText() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Returns the tip text for this property

numLeaves() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns number of leaves in tree structure.

numLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns the number of leaves (normal count).

numLeaves(int) - Method in class weka.classifiers.trees.m5.RuleNode

Sets the leaves' numbers

numNeighboursTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the tip text for this property

numNodes() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns number of nodes in tree structure.

numNodes() - Method in class weka.classifiers.trees.lmt.LMTNode

Returns the number of nodes.

numNodes() - Method in class weka.classifiers.trees.REPTree

Computes size of the tree.

numNonZero() - Method in class weka.core.pmml.SparseArray

Get the number of non-zero values in this sparse array

numNumericTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1

Returns the tip text for this property

numParameters() - Method in class weka.classifiers.functions.LinearRegression

Get the number of coefficients used in the model

numParameters() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel

Return the number of parameters (coefficients) in the linear model

numPendingOutput() - Method in class weka.filters.Filter

Returns the number of instances pending output

numPendingOutput() - Method in class weka.filters.unsupervised.attribute.RemoveType

Returns the number of instances pending output

numRepositoryPackages() - Static method in class weka.core.WekaPackageManager

Get the number of packages that are available at the repository.

numRows() - Method in class weka.classifiers.CostMatrix

Same as size

numRows() - Method in class weka.core.Matrix

Deprecated. Returns the number of rows in the matrix.

numRules() - Method in class weka.classifiers.rules.part.MakeDecList

Outputs the number of rules in the classifier.

numRulesTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

numRulesToFindTipText() - Method in class weka.associations.FPGrowth

Tip text for this property suitable for displaying in the GUI.

numRunsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Returns the tip text for this property

numSplits() - Method in class weka.classifiers.trees.ht.SplitCandidate

Number of branches resulting from the split

numSubsets() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Returns the number of created subsets for the split.

numThreadsTipText() - Method in class weka.attributeSelection.CfsSubsetEval

numToSelectTipText() - Method in class weka.attributeSelection.GreedyStepwise

Returns the tip text for this property

numToSelectTipText() - Method in class weka.attributeSelection.Ranker

Returns the tip text for this property

numTreesTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

numTrueNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate the number of true negatives with respect to a particular class.

numTrueNegatives(int) - Method in class weka.classifiers.Evaluation

Calculate the number of true negatives with respect to a particular class.

numTruePositives(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate the number of true positives with respect to a particular class.

numTruePositives(int) - Method in class weka.classifiers.Evaluation

Calculate the number of true positives with respect to a particular class.

numValues() - Method in class weka.core.Attribute

Returns the number of attribute values.

numValues() - Method in class weka.core.DenseInstance

Returns the number of values present.

numValues() - Method in interface weka.core.Instance

Returns the number of values present in a sparse representation.

numValues() - Method in class weka.core.pmml.Array

Get the number of values in this array.

numValues() - Method in class weka.core.pmml.SparseArray

Get the number of values in this array.

numValues() - Method in class weka.core.SparseInstance

Returns the number of values in the sparse vector.

numValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Returns the tip text for this property

O

Obfuscate - Class in weka.filters.unsupervised.attribute

A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values.

Obfuscate() - Constructor for class weka.filters.unsupervised.attribute.Obfuscate

ObjectFactory - Class in weka.core.pmml.jaxbbindings

This object contains factory methods for each Java content interface and Java element interface generated in the weka.core.pmml.jaxbbindings package.

ObjectFactory() - Constructor for class weka.core.pmml.jaxbbindings.ObjectFactory

Create a new ObjectFactory that can be used to create new instances of schema derived classes for package: weka.core.pmml.jaxbbindings

obtainVotes(Instance) - Method in class weka.classifiers.functions.SMO

Returns an array of votes for the given instance.

OFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

OFF - Static variable in class weka.core.Debug

the log level Off - i.e., no logging

OffscreenChartRenderer - Interface in weka.gui.beans

Interface to something that can render certain types of charts in headless mode.

oldEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit

Computes entropy of distribution before splitting.

omegaTipText() - Method in class weka.classifiers.functions.supportVector.Puk

Returns the tip text for this property

ON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

Some usefull constants

onDemandDirectoryTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier

onDemandDirectoryTipText() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns the tip text for this property

OneR - Class in weka.classifiers.rules

Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.

OneR() - Constructor for class weka.classifiers.rules.OneR

OneRAttributeEval - Class in weka.attributeSelection

OneRAttributeEval :

Evaluates the worth of an attribute by using the OneR classifier.

Valid options are:

OneRAttributeEval() - Constructor for class weka.attributeSelection.OneRAttributeEval

Constructor

onUnit(Graphics, int, int, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection

Call this function to determine if the point at x,y is on the unit.

open(File) - Method in class weka.gui.scripting.FileScriptingPanel

Opens the specified file.

open(File) - Method in class weka.gui.scripting.Script

Tries to open the file.

openFrame(String) - Method in class weka.gui.ResultHistoryPanel

Opens the named result in a separate frame.

openURL(String) - Static method in class weka.gui.BrowserHelper

opens the URL in a browser.

openURL(Component, String) - Static method in class weka.gui.BrowserHelper

opens the URL in a browser.

openURL(Component, String, boolean) - Static method in class weka.gui.BrowserHelper

opens the URL in a browser.

Optimization - Class in weka.core

Implementation of Active-sets method with BFGS update to solve optimization problem with only bounds constraints in multi-dimensions.

Optimization() - Constructor for class weka.core.Optimization

optimizationsTipText() - Method in class weka.classifiers.rules.JRip

Returns the tip text for this property

optimize() - Method in class weka.classifiers.functions.supportVector.RegSMO

finds alpha and alpha* parameters that optimize the SVM target function

OptimumLiftGraph - Class in weka.core.pmml.jaxbbindings

Java class for OptimumLiftGraph element declaration.

OptimumLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.OptimumLiftGraph

Option - Class in weka.core

Class to store information about an option.

Option(String, String, int, String) - Constructor for class weka.core.Option

Creates new option with the given parameters.

OptionHandler - Interface in weka.core

Interface to something that understands options.

OptionHandlerJavadoc - Class in weka.core

Generates Javadoc comments from the OptionHandler's options.

OptionHandlerJavadoc() - Constructor for class weka.core.OptionHandlerJavadoc

default constructor

OPTIONS_ENDTAG - Static variable in class weka.core.OptionHandlerJavadoc

the end comment tag for inserting the generated Javadoc

OPTIONS_STARTTAG - Static variable in class weka.core.OptionHandlerJavadoc

the start comment tag for inserting the generated Javadoc

optionsTipTextHTML() - Method in class weka.gui.beans.AbstractOffscreenChartRenderer

Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form.

optionsTipTextHTML() - Method in interface weka.gui.beans.OffscreenChartRenderer

Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form

optionsTipTextHTML() - Method in class weka.gui.beans.WekaOffscreenChartRenderer

Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form

OPTYPE - Enum in weka.core.pmml.jaxbbindings

Java class for OPTYPE.

or(Capabilities) - Method in class weka.core.Capabilities

performs an OR conjunction with the capabilities of the given Capabilities object and updates itself

OR - Static variable in interface weka.core.mathematicalexpression.sym

OR - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

ORDERED - Static variable in class weka.datagenerators.clusterers.BIRCHCluster

Constant set for input order (option O)

ordering() - Method in class weka.core.Attribute

Returns the ordering of the attribute.

ORDERING_MODULO - Static variable in class weka.core.Attribute

Constant set for modulo-ordered attributes.

ORDERING_ORDERED - Static variable in class weka.core.Attribute

Constant set for ordered attributes.

ORDERING_SYMBOLIC - Static variable in class weka.core.Attribute

Constant set for symbolic attributes.

orderTipText() - Method in class weka.core.MinkowskiDistance

Returns the tip text for this property.

originalValue(double) - Method in class weka.filters.supervised.attribute.ClassOrder

Return the original internal class value given the randomized class value, i.e.

OUT_OF_MEMORY_THRESHOLD - Static variable in class weka.core.Memory

outcomes - Variable in class weka.gui.graphvisualizer.GraphNode

The outcomes for the given node

outlierFactorTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns the tip text for this property

OUTLIERTREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for OUTLIER-TREATMENT-METHOD.

OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is an output unit.

Output - Class in weka.core.pmml.jaxbbindings

Java class for Output element declaration.

Output() - Constructor for class weka.core.pmml.jaxbbindings.Output

output() - Method in class weka.filters.Filter

Output an instance after filtering and remove from the output queue.

output() - Method in class weka.filters.unsupervised.attribute.RemoveType

Output an instance after filtering and remove from the output queue.

outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.LinearRegression

Returns the tip text for this property.

outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.SimpleLinearRegression

Returns the tip text for this property.

outputClassificationTipText() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the tip text for this property.

outputDetailedInfoTipText() - Method in class weka.attributeSelection.CorrelationAttributeEval

Returns the tip text for this property

outputDistributionTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the tip text for this property.

outputDistributionTipText() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the tip text for this property.

outputErrorFlagTipText() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the tip text for this property.

OutputField - Class in weka.core.pmml.jaxbbindings

Java class for OutputField element declaration.

OutputField() - Constructor for class weka.core.pmml.jaxbbindings.OutputField

outputFileName() - Method in class weka.experiment.CSVResultListener

Get the value of OutputFileName.

outputFilenameTipText() - Method in class weka.core.converters.TextDirectoryLoader

the tip text for this property

outputFileTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the tip text for this property.

outputFileTipText() - Method in class weka.experiment.CrossValidationResultProducer

Returns the tip text for this property

outputFileTipText() - Method in class weka.experiment.CSVResultListener

Returns the tip text for this property

outputFileTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

outputFileTipText() - Method in class weka.experiment.RandomSplitResultProducer

Returns the tip text for this property

outputFormat() - Method in class weka.gui.streams.InstanceJoiner

Gets the format of the output instances.

outputFormat() - Method in class weka.gui.streams.InstanceLoader

outputFormat() - Method in interface weka.gui.streams.InstanceProducer

OutputFormatDialog - Class in weka.gui.experiment

A dialog for setting various output format parameters.

OutputFormatDialog(Frame) - Constructor for class weka.gui.experiment.OutputFormatDialog

initializes the dialog with the given parent frame.

outputItemSetsTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

OutputLogger - Class in weka.core.logging

A logger that logs all output on stdout and stderr to a file.

OutputLogger() - Constructor for class weka.core.logging.OutputLogger

OutputLogger.OutputPrintStream - Class in weka.core.logging

A print stream class to capture all data from stdout and stderr.

OutputLogger.OutputPrintStream(OutputLogger, PrintStream) - Constructor for class weka.core.logging.OutputLogger.OutputPrintStream

Default constructor.

outputOffsetMultiplierTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Returns the tip text for this property

outputPeek() - Method in class weka.filters.Filter

Output an instance after filtering but do not remove from the output queue.

outputPeek() - Method in class weka.filters.unsupervised.attribute.RemoveType

Output an instance after filtering but do not remove from the output queue.

outputPeek() - Method in class weka.gui.streams.InstanceJoiner

Output an instance after filtering but do not remove from the output queue.

outputPeek() - Method in class weka.gui.streams.InstanceLoader

outputPeek() - Method in interface weka.gui.streams.InstanceProducer

outputPerClassInfoRetrievalStatsTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Return a tip text string for this property

outputProbsForSVMTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

outputs(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection

Returns a vector of BeanInstances that can be considered as outputs (or the right-hand side of a sub-flow)

outputsContains(BeanInstance) - Method in class weka.gui.beans.MetaBean

outputTipText() - Method in class weka.datagenerators.DataGenerator

Returns the tip text for this property

outputTypeSet(int) - Method in class weka.core.Debug.DBO

Return true if the outputtype is set

outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit

This function calculates what the output value should be.

outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection

Call this to get the output value of this unit.

outputValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod

This function calculates what the output value should be.

outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode

Call this to get the output value of this unit.

outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit

This function calculates what the output value should be.

outputWordCountsTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

OutputZipper - Class in weka.experiment

OutputZipper writes output to either gzipped files or to a multi entry zip file.

OutputZipper(File) - Constructor for class weka.experiment.OutputZipper

Constructor.

OVAL - Static variable in class weka.gui.visualize.VisualizePanelEvent

P

p(String) - Static method in class weka.core.Debug.DBO

prints out text.

p() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode

Returns the instance represented by the node.

p1evl(double, double[], int) - Static method in class weka.core.Statistics

Evaluates the given polynomial of degree N at x.

PACKAGE - Static variable in class weka.core.stemmers.SnowballStemmer

the package name for snowball.

PACKAGE_EXT - Static variable in class weka.core.stemmers.SnowballStemmer

the package name where the stemmers are located.

PackageManager - Class in weka.gui

A GUI interface the the package management system.

PackageManager() - Constructor for class weka.gui.PackageManager

packages() - Method in class weka.core.ClassCache

Returns all the stored packages.

PACKAGES_DIR - Static variable in class weka.core.WekaPackageManager

The default packages directory

pad(String, String, int, boolean) - Static method in class weka.core.pmml.PMMLUtils

Utility method to left or right pad strings with arbitrary characters.

padLeft(String, int) - Static method in class weka.core.Utils

Pads a string to a specified length, inserting spaces on the left as required.

padRight(String, int) - Static method in class weka.core.Utils

Pads a string to a specified length, inserting spaces on the right as required.

PAGE_HEADER - Static variable in class weka.gui.PackageManager

paint(Graphics) - Method in class weka.gui.ETable

Paints empty rows too, after letting the UI delegate do its painting.

paint(Graphics) - Method in class weka.gui.SplashWindow

Paints the image on the window.

paintBorder(Component, Graphics, int, int, int, int) - Method in class weka.gui.beans.ShadowBorder

Paints the drop shadow border around the given component.

paintComponent(Graphics) - Method in class weka.gui.AttributeVisualizationPanel

Paints this component

paintComponent(Graphics) - Method in class weka.gui.beans.BeanVisual

paintComponent(Graphics) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer

Updates the screen contents.

paintComponent(Graphics) - Method in class weka.gui.Main.BackgroundDesktopPane

draws the background image.

paintComponent(Graphics) - Method in class weka.gui.MemoryUsagePanel

draws the background image.

paintComponent(Graphics) - Method in class weka.gui.PropertyPanel

Paints the component, using the property editor's paint method.

paintComponent(Graphics) - Method in class weka.gui.treevisualizer.TreeVisualizer

Updates the screen contents.

paintComponent(Graphics) - Method in class weka.gui.visualize.ClassPanel

Renders this component

paintComponent(Graphics) - Method in class weka.gui.visualize.Plot2D

Renders this component

paintConnections(Graphics, Integer...) - Static method in class weka.gui.beans.BeanConnection

Renders the connections and their names on the supplied graphics context

paintLabels(Graphics, Integer...) - Static method in class weka.gui.beans.BeanInstance

Renders the textual labels for the beans.

paintValue(Graphics, Rectangle) - Method in class weka.gui.beans.EnvironmentField

paintValue(Graphics, Rectangle) - Method in class weka.gui.CostMatrixEditor

Paints a graphical representation of the object.

paintValue(Graphics, Rectangle) - Method in class weka.gui.FileEditor

Paints a representation of the current Object.

paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericArrayEditor

Paints a representation of the current classifier.

paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericObjectEditor

Paints a representation of the current Object.

paintValue(Graphics, Rectangle) - Method in class weka.gui.SimpleDateFormatEditor

Paints a graphical representation of the object.

PairCounts - Class in weka.core.pmml.jaxbbindings

Java class for PairCounts element declaration.

PairCounts() - Constructor for class weka.core.pmml.jaxbbindings.PairCounts

PairedCorrectedTTester - Class in weka.experiment

Behaves the same as PairedTTester, only it uses the corrected resampled t-test statistic.

PairedCorrectedTTester() - Constructor for class weka.experiment.PairedCorrectedTTester

PairedStats - Class in weka.experiment

A class for storing stats on a paired comparison (t-test and correlation)

PairedStats(double) - Constructor for class weka.experiment.PairedStats

Creates a new PairedStats object with the supplied significance level.

PairedStatsCorrected - Class in weka.experiment

A class for storing stats on a paired comparison.

PairedStatsCorrected(double, double) - Constructor for class weka.experiment.PairedStatsCorrected

Creates a new PairedStatsCorrected object with the supplied significance level and train/test ratio.

PairedTTester - Class in weka.experiment

Calculates T-Test statistics on data stored in a set of instances.

PairedTTester() - Constructor for class weka.experiment.PairedTTester

pairwiseCoupling(double[][], double[][]) - Static method in class weka.classifiers.meta.MultiClassClassifier

Implements pairwise coupling.

ParallelIteratedSingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.

ParallelIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

ParallelMultipleClassifiersCombiner - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers.

ParallelMultipleClassifiersCombiner() - Constructor for class weka.classifiers.ParallelMultipleClassifiersCombiner

Parameter - Class in weka.core.pmml.jaxbbindings

Java class for Parameter element declaration.

Parameter() - Constructor for class weka.core.pmml.jaxbbindings.Parameter

ParameterField - Class in weka.core.pmml.jaxbbindings

Java class for ParameterField element declaration.

ParameterField() - Constructor for class weka.core.pmml.jaxbbindings.ParameterField

ParameterList - Class in weka.core.pmml.jaxbbindings

Java class for ParameterList element declaration.

ParameterList() - Constructor for class weka.core.pmml.jaxbbindings.ParameterList

ParamMatrix - Class in weka.core.pmml.jaxbbindings

Java class for ParamMatrix element declaration.

ParamMatrix() - Constructor for class weka.core.pmml.jaxbbindings.ParamMatrix

parentClass - Variable in class weka.experiment.PropertyNode

The class of the object with this property

parentNode() - Method in class weka.classifiers.trees.m5.RuleNode

Get the parent of this node

ParentSet - Class in weka.classifiers.bayes.net

Helper class for Bayes Network classifiers.

ParentSet() - Constructor for class weka.classifiers.bayes.net.ParentSet

default constructor

ParentSet(int) - Constructor for class weka.classifiers.bayes.net.ParentSet

constructor

ParentSet(ParentSet) - Constructor for class weka.classifiers.bayes.net.ParentSet

copy constructor

parentTipText() - Method in class weka.datagenerators.ClusterDefinition

Returns the tip text for this property

parentValue() - Method in class weka.gui.HierarchyPropertyParser

The value in the parent node.

parse() - Method in class weka.gui.graphvisualizer.BIFParser

This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors

parse() - Method in class weka.gui.graphvisualizer.DotParser

This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors

parseDate(String) - Method in class weka.core.Attribute

Parses the given String as Date, according to the current format and returns the corresponding amount of milliseconds.

parseMatlab(String) - Static method in class weka.classifiers.CostMatrix

creates a matrix from the given Matlab string.

parseMatlab(String) - Static method in class weka.core.matrix.Matrix

creates a matrix from the given Matlab string.

parseMatlab(String) - Static method in class weka.core.Matrix

Deprecated. creates a matrix from the given Matlab string.

parsePath(String) - Static method in class weka.core.PropertyPath.Path

returns a path object based on the given path string

Parser - Class in weka.core.json

CUP v0.11a beta 20060608 generated parser.

Parser() - Constructor for class weka.core.json.Parser

Default constructor.

Parser(Scanner) - Constructor for class weka.core.json.Parser

Constructor which sets the default scanner.

Parser(Scanner, SymbolFactory) - Constructor for class weka.core.json.Parser

Constructor which sets the default scanner.

Parser - Class in weka.core.mathematicalexpression

CUP v0.11a beta 20060608 generated parser.

Parser() - Constructor for class weka.core.mathematicalexpression.Parser

Default constructor.

Parser(Scanner) - Constructor for class weka.core.mathematicalexpression.Parser

Constructor which sets the default scanner.

Parser(Scanner, SymbolFactory) - Constructor for class weka.core.mathematicalexpression.Parser

Constructor which sets the default scanner.

Parser - Class in weka.filters.unsupervised.instance.subsetbyexpression

CUP v0.11a beta 20060608 generated parser.

Parser() - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Default constructor.

Parser(Scanner) - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Constructor which sets the default scanner.

Parser(Scanner, SymbolFactory) - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Constructor which sets the default scanner.

PART - Class in weka.classifiers.rules

Class for generating a PART decision list.

PART() - Constructor for class weka.classifiers.rules.PART

partition(Instances, int) - Static method in class weka.classifiers.rules.RuleStats

Patition the data into 2, first of which has (numFolds-1)/numFolds of the data and the second has 1/numFolds of the data

Partition - Class in weka.core.pmml.jaxbbindings

Java class for Partition element declaration.

Partition() - Constructor for class weka.core.pmml.jaxbbindings.Partition

PartitionedMultiFilter - Class in weka.filters.unsupervised.attribute

A filter that applies filters on subsets of attributes and assembles the output into a new dataset.

PartitionedMultiFilter() - Constructor for class weka.filters.unsupervised.attribute.PartitionedMultiFilter

PartitionFieldStats - Class in weka.core.pmml.jaxbbindings

Java class for PartitionFieldStats element declaration.

PartitionFieldStats() - Constructor for class weka.core.pmml.jaxbbindings.PartitionFieldStats

PartitionGenerator - Interface in weka.core

This interface can be implemented by algorithms that generate a partition of the instance space (e.g., decision trees).

partitionGeneratorTipText() - Method in class weka.filters.supervised.attribute.PartitionMembership

Returns a description of this option suitable for display as a tip text in the gui.

PartitionMembership - Class in weka.filters.supervised.attribute

A filter that uses a PartitionGenerator to generate partition membership values; filtered instances are composed of these values plus the class attribute (if set in the input data) and rendered as sparse instances.

PartitionMembership() - Constructor for class weka.filters.supervised.attribute.PartitionMembership

partitionOptions(String[]) - Static method in class weka.classifiers.bayes.BayesNet

Returns the secondary set of options (if any) contained in the supplied options array.

partitionOptions(String[]) - Static method in class weka.core.Utils

Returns the secondary set of options (if any) contained in the supplied options array.

passesTest(Instance) - Method in class weka.datagenerators.Test

Determines whether an instance passes the test.

passwordTipText() - Method in class weka.core.converters.DatabaseLoader

the tip text for this property

passwordTipText() - Method in class weka.core.converters.DatabaseSaver

Returns the tip text for this property.

passwordTipText() - Method in class weka.experiment.DatabaseUtils

Returns the tip text for this property.

paste(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

Apply paste operation with XMLBIF fragment.

pattern(int, int) - Static method in class weka.core.matrix.FloatingPointFormat

patternTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster

Returns the tip text for this property

PCell - Class in weka.core.pmml.jaxbbindings

Java class for PCell element declaration.

PCell() - Constructor for class weka.core.pmml.jaxbbindings.PCell

PCell(String, String, BigInteger, double) - Constructor for class weka.core.pmml.jaxbbindings.PCell

pchisq(double) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of the Chi-squared distribution

pchisq(double, double) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of the noncentral Chi-squared distribution.

pchisq(double, DoubleVector) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of a set of noncentral Chi-squared distributions.

PCovCell - Class in weka.core.pmml.jaxbbindings

Java class for PCovCell element declaration.

PCovCell() - Constructor for class weka.core.pmml.jaxbbindings.PCovCell

PCovMatrix - Class in weka.core.pmml.jaxbbindings

Java class for PCovMatrix element declaration.

PCovMatrix() - Constructor for class weka.core.pmml.jaxbbindings.PCovMatrix

pctCorrect() - Method in class weka.classifiers.evaluation.Evaluation

Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).

pctCorrect() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).

pctIncorrect() - Method in class weka.classifiers.evaluation.Evaluation

Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).

pctIncorrect() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).

pctUnclassified() - Method in class weka.classifiers.evaluation.Evaluation

Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).

pctUnclassified() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).

peek() - Method in class weka.core.Queue

Gets object from the front of the queue.

PENTAHO_IMAGE1 - Static variable in class weka.core.RepositoryIndexGenerator

PENTAHO_IMAGE2 - Static variable in class weka.core.RepositoryIndexGenerator

perBag(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances in given bag.

percentageTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns the tip text for this property

percentAttributesUsed() - Method in class weka.classifiers.trees.lmt.LogisticBase

Returns the fraction of all attributes in the data that are used in the logistic model (in percent).

percentTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

percentTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the tip text for this property

perClass(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances of given class.

perClassPerBag(int, int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances of given class in given bag.

PerformanceStats - Class in weka.core.neighboursearch

The class that measures the performance of a nearest neighbour search (NNS) algorithm.

PerformanceStats() - Constructor for class weka.core.neighboursearch.PerformanceStats

default constructor.

performRequest(String) - Method in class weka.gui.beans.Associator

Perform a particular request

performRequest(String) - Method in class weka.gui.beans.AttributeSummarizer

Perform a named user request

performRequest(String) - Method in class weka.gui.beans.Classifier

Perform a particular request

performRequest(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Perform the named request

performRequest(String) - Method in class weka.gui.beans.Clusterer

Perform a particular request

performRequest(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Perform the named request

performRequest(String) - Method in class weka.gui.beans.CostBenefitAnalysis

performRequest(String) - Method in class weka.gui.beans.CrossValidationFoldMaker

Perform the named request

performRequest(String) - Method in class weka.gui.beans.DataVisualizer

Describe performRequest method here.

performRequest(String) - Method in class weka.gui.beans.Filter

Perform the named request

performRequest(String) - Method in class weka.gui.beans.GraphViewer

Perform the named request

performRequest(String) - Method in class weka.gui.beans.ImageViewer

performRequest(String) - Method in class weka.gui.beans.MetaBean

Perform a particular request

performRequest(String) - Method in class weka.gui.beans.ModelPerformanceChart

Describe performRequest method here.

performRequest(String) - Method in class weka.gui.beans.ScatterPlotMatrix

Perform a named user request

performRequest(String) - Method in class weka.gui.beans.StripChart

Describe performRequest method here.

performRequest(String) - Method in class weka.gui.beans.TextViewer

Perform the named request

performRequest(String) - Method in class weka.gui.beans.TrainTestSplitMaker

Perform the named request

performRequest(String) - Method in interface weka.gui.beans.UserRequestAcceptor

Perform the named request

periodicPruningRateTipText() - Method in class weka.clusterers.Canopy

Returns the tip text for this property.

periodicPruningTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property

periodicPruningTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property

periodicPruningTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

perturbationFractionTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns the tip text for this property

phaseIID(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al.

phaseIIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al.

phaseIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al.

PI - Static variable in class weka.core.xml.XMLDocument

the parsing instructions "<?xml version=\"1.0\" encoding=\"utf-8\"?>" (may not show up in Javadoc due to tags!).

PKIDiscretize - Class in weka.filters.unsupervised.attribute

Discretizes numeric attributes using equal frequency binning, where the number of bins is equal to the square root of the number of non-missing values.

For more information, see:

Ying Yang, Geoffrey I.

PKIDiscretize() - Constructor for class weka.filters.unsupervised.attribute.PKIDiscretize

place(Node) - Method in interface weka.gui.treevisualizer.NodePlace

The function to call to postion the tree that starts at Node r

place(Node) - Method in class weka.gui.treevisualizer.PlaceNode1

Call this function to have each node in the tree starting at 'r' placed in a visual (not logical, they already are) tree position.

place(Node) - Method in class weka.gui.treevisualizer.PlaceNode2

The Funtion to call to have the nodes arranged.

PlaceNode1 - Class in weka.gui.treevisualizer

This class will place the Nodes of a tree.

PlaceNode1() - Constructor for class weka.gui.treevisualizer.PlaceNode1

PlaceNode2 - Class in weka.gui.treevisualizer

This class will place the Nodes of a tree.

PlaceNode2() - Constructor for class weka.gui.treevisualizer.PlaceNode2

PlainText - Class in weka.classifiers.evaluation.output.prediction

Outputs the predictions in plain text.

PlainText() - Constructor for class weka.classifiers.evaluation.output.prediction.PlainText

PLAINTEXT_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc

the end comment tag for inserting the generated BibTex

PLAINTEXT_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc

the start comment tag for inserting the generated BibTex

pln(String) - Static method in class weka.core.Debug.DBO

prints out text + endofline.

Plot2D - Class in weka.gui.visualize

This class plots datasets in two dimensions.

Plot2D() - Constructor for class weka.gui.visualize.Plot2D

Constructor

Plot2DCompanion - Interface in weka.gui.visualize

Interface for classes that need to draw to the Plot2D panel *before* Plot2D renders anything (eg.

PlotData2D - Class in weka.gui.visualize

This class is a container for plottable data.

PlotData2D(Instances) - Constructor for class weka.gui.visualize.PlotData2D

Construct a new PlotData2D using the supplied instances

plotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Render the training points on-screen.

plotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Plots the training data on-screen.

PluginManager - Class in weka.gui.beans

Class that manages a global map of plugins.

PluginManager() - Constructor for class weka.gui.beans.PluginManager

PLURAL_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants

PLURAL_DUMMY node - node with more than one outgoing edge i.e.

PLUS - Static variable in interface weka.core.mathematicalexpression.sym

plus(double) - Method in class weka.core.matrix.DoubleVector

Adds a value to all the elements

plus(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Adds another vector element by element

plus(Matrix) - Method in class weka.core.matrix.Matrix

C = A + B

PLUS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

PLUS_SHAPE - Static variable in class weka.gui.visualize.Plot2D

plusEquals(double) - Method in class weka.core.matrix.DoubleVector

Adds a value to all the elements in place

plusEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Adds another vector in place element by element

plusEquals(Matrix) - Method in class weka.core.matrix.Matrix

A = A + B

pmiss - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry

transformation probability to missing value

PMML - Class in weka.core.pmml.jaxbbindings

Java class for PMML element declaration.

PMML() - Constructor for class weka.core.pmml.jaxbbindings.PMML

PMML_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClassifierPanel

The filename extension that should be used for PMML xml files.

PMML_VERSION - Static variable in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper

PMML version that the jaxbbindings were created from

PMMLClassifier - Class in weka.classifiers.pmml.consumer

Abstract base class for all PMML classifiers.

PMMLFactory - Class in weka.core.pmml

This class is a factory class for reading/writing PMML models

PMMLFactory() - Constructor for class weka.core.pmml.PMMLFactory

PMMLModel - Interface in weka.core.pmml

Interface for all PMML models

PMMLProducer - Interface in weka.core.pmml

Interface to something that can produce a PMML representation of itself.

PMMLUtils - Class in weka.core.pmml

Utility routines.

PMMLUtils() - Constructor for class weka.core.pmml.PMMLUtils

PNGWriter - Class in weka.gui.visualize

This class takes any JComponent and outputs it to a PNG-file.

PNGWriter() - Constructor for class weka.gui.visualize.PNGWriter

initializes the object.

PNGWriter(JComponent) - Constructor for class weka.gui.visualize.PNGWriter

initializes the object with the given Component.

PNGWriter(JComponent, File) - Constructor for class weka.gui.visualize.PNGWriter

initializes the object with the given Component and filename.

pnorm(double) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of the standard normal.

pnorm(double, double, double) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of a normal distribution.

pnorm(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths

Returns the cumulative probability of a set of normal distributions with different means.

POINT - Static variable in class weka.core.Version

point revision

PointsClosestToFurthestChildren - Class in weka.core.neighboursearch.balltrees

Implements the Moore's method to split a node of a ball tree.

For more information please see section 2 of the 1st and 3.2.3 of the 2nd:

Andrew W.

PointsClosestToFurthestChildren() - Constructor for class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Constructor.

PointsClosestToFurthestChildren(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Constructor.

PoissonDistribution - Class in weka.core.pmml.jaxbbindings

Java class for PoissonDistribution element declaration.

PoissonDistribution() - Constructor for class weka.core.pmml.jaxbbindings.PoissonDistribution

PoissonEstimator - Class in weka.estimators

Simple probability estimator that places a single Poisson distribution over the observed values.

PoissonEstimator() - Constructor for class weka.estimators.PoissonEstimator

polevl(double, double[], int) - Static method in class weka.core.Statistics

Evaluates the given polynomial of degree N at x.

POLYGON - Static variable in class weka.gui.visualize.VisualizePanelEvent

PolyKernel - Class in weka.classifiers.functions.supportVector

The polynomial kernel : K(x, y) = <x, y>^p or K(x, y) = (<x, y>+1)^p

Valid options are:

PolyKernel() - Constructor for class weka.classifiers.functions.supportVector.PolyKernel

default constructor - does nothing.

PolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.PolyKernel

Creates a new PolyKernel instance.

PolynomialKernelType - Class in weka.core.pmml.jaxbbindings

Java class for PolynomialKernelType element declaration.

PolynomialKernelType() - Constructor for class weka.core.pmml.jaxbbindings.PolynomialKernelType

poolSizeTipText() - Method in class weka.attributeSelection.CfsSubsetEval

pop() - Method in class weka.core.neighboursearch.covertrees.Stack

Pops (removes) the first (last added) element in the stack.

pop() - Method in class weka.core.Queue

Pops an object from the front of the queue.

populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

position() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the position of the split in the sorted values.

position() - Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the position of the split in the sorted values.

position() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the position of the split in the sorted values.

positiveIndexTipText() - Method in class weka.associations.FPGrowth

Tip text for this property suitable for displaying in the GUI.

postProcess(int[]) - Method in class weka.attributeSelection.ASEvaluation

Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.

postProcess(int[]) - Method in class weka.attributeSelection.CfsSubsetEval

Calls locallyPredictive in order to include locally predictive attributes (if requested).

postProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.AveragingResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess() - Method in class weka.experiment.CrossValidationResultProducer

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.DatabaseResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess() - Method in class weka.experiment.Experiment

Signals that the experiment is finished running, so that cleanup can be done.

postProcess() - Method in class weka.experiment.ExplicitTestsetResultProducer

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.LearningRateResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess() - Method in class weka.experiment.RandomSplitResultProducer

Perform any postprocessing.

postProcess() - Method in class weka.experiment.RemoteExperiment

overides the one in Experiment

postProcess(ResultProducer) - Method in interface weka.experiment.ResultListener

Perform any postprocessing.

postProcess() - Method in interface weka.experiment.ResultProducer

Perform any postprocessing.

postProcessDistances(double[]) - Method in interface weka.core.DistanceFunction

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessDistances(double[]) - Method in class weka.core.EuclideanDistance

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessDistances(double[]) - Method in class weka.core.MinkowskiDistance

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessDistances(double[]) - Method in class weka.core.NormalizableDistance

Does nothing, derived classes may override it though.

PostscriptGraphics - Class in weka.gui.visualize

The PostscriptGraphics class extends the Graphics2D class to produce an encapsulated postscript file rather than on-screen display.

PostscriptGraphics(int, int, OutputStream) - Constructor for class weka.gui.visualize.PostscriptGraphics

Constructor Creates a new PostscriptGraphics object, given dimensions and output file.

PostscriptWriter - Class in weka.gui.visualize

This class takes any Component and outputs it to a Postscript file.

PostscriptWriter() - Constructor for class weka.gui.visualize.PostscriptWriter

initializes the object

PostscriptWriter(JComponent) - Constructor for class weka.gui.visualize.PostscriptWriter

initializes the object with the given Component

PostscriptWriter(JComponent, File) - Constructor for class weka.gui.visualize.PostscriptWriter

initializes the object with the given Component and filename

potential(int, double, double[], double[], boolean) - Method in class weka.classifiers.rules.RuleStats

Calculate the potential to decrease DL of the ruleset, i.e.

PotentialClassIgnorer - Class in weka.filters.unsupervised.attribute

This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required.

PotentialClassIgnorer() - Constructor for class weka.filters.unsupervised.attribute.PotentialClassIgnorer

POW - Static variable in interface weka.core.mathematicalexpression.sym

POW - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

powerSeries(double, double, double) - Static method in class weka.core.Statistics

Power series for incomplete beta integral.

PPCell - Class in weka.core.pmml.jaxbbindings

Java class for PPCell element declaration.

PPCell() - Constructor for class weka.core.pmml.jaxbbindings.PPCell

PPMatrix - Class in weka.core.pmml.jaxbbindings

Java class for PPMatrix element declaration.

PPMatrix() - Constructor for class weka.core.pmml.jaxbbindings.PPMatrix

preBuiltClassifiersTipText() - Method in class weka.classifiers.meta.Vote

Returns the tip text for this property

precision(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate the precision with respect to a particular class.

precision(int) - Method in class weka.classifiers.Evaluation

Calculate the precision with respect to a particular class.

PRECISION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

attribute name: Precision

preComputeCorrelationMatrixTipText() - Method in class weka.attributeSelection.CfsSubsetEval

PrecomputedKernelMatrixKernel - Class in weka.classifiers.functions.supportVector

This kernel is based on a static kernel matrix that is read from a file.

PrecomputedKernelMatrixKernel() - Constructor for class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

PreConstructedLinearModel - Class in weka.classifiers.trees.m5

This class encapsulates a linear regression function.

PreConstructedLinearModel(double[], double) - Constructor for class weka.classifiers.trees.m5.PreConstructedLinearModel

Constructor

predicted() - Method in class weka.classifiers.evaluation.NominalPrediction

Gets the predicted class value.

predicted() - Method in class weka.classifiers.evaluation.NumericPrediction

Gets the predicted class value.

predicted() - Method in interface weka.classifiers.evaluation.Prediction

Gets the predicted class value.

predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcesses

Computes a prediction interval for the given instance and confidence level.

predictIntervals(Instance, double) - Method in interface weka.classifiers.IntervalEstimator

Returns an N * 2 array, where N is the number of prediction intervals.

predictIntervals(Instance, double) - Method in class weka.classifiers.meta.RegressionByDiscretization

Returns an N * 2 array, where N is the number of prediction intervals.

predictIntervals(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Returns the interval for the given confidence value.

predictIntervals(double) - Method in interface weka.estimators.UnivariateIntervalEstimator

Returns the intervals at the given confidence value.

predictIntervals(double) - Method in class weka.estimators.UnivariateKernelEstimator

Returns the interval for the given confidence value.

predictIntervals(double) - Method in class weka.estimators.UnivariateNormalEstimator

Returns the interval for the given confidence value.

Prediction - Interface in weka.classifiers.evaluation

Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.

PredictionAppender - Class in weka.gui.beans

Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.

PredictionAppender() - Constructor for class weka.gui.beans.PredictionAppender

Creates a new PredictionAppender instance.

PredictionAppenderBeanInfo - Class in weka.gui.beans

Bean info class for PredictionAppender.

PredictionAppenderBeanInfo() - Constructor for class weka.gui.beans.PredictionAppenderBeanInfo

PredictionAppenderCustomizer - Class in weka.gui.beans

GUI Customizer for the prediction appender bean

PredictionAppenderCustomizer() - Constructor for class weka.gui.beans.PredictionAppenderCustomizer

predictionIntervals() - Method in class weka.classifiers.evaluation.NumericPrediction

Returns the predictions intervals.

predictions() - Method in class weka.classifiers.evaluation.Evaluation

Returns the predictions that have been collected.

predictions() - Method in class weka.classifiers.Evaluation

Returns the predictions that have been collected.

PredictiveModelQuality - Class in weka.core.pmml.jaxbbindings

Java class for PredictiveModelQuality element declaration.

PredictiveModelQuality() - Constructor for class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Predictor - Class in weka.core.pmml.jaxbbindings

Java class for Predictor element declaration.

Predictor() - Constructor for class weka.core.pmml.jaxbbindings.Predictor

PredictorTerm - Class in weka.core.pmml.jaxbbindings

Java class for PredictorTerm element declaration.

PredictorTerm() - Constructor for class weka.core.pmml.jaxbbindings.PredictorTerm

predictQuantile(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Returns the quantile for the given percentage.

predictQuantile(double) - Method in class weka.estimators.UnivariateKernelEstimator

Returns the quantile for the given percentage.

predictQuantile(double) - Method in class weka.estimators.UnivariateNormalEstimator

Returns the quantile for the given percentage.

predictQuantile(double) - Method in interface weka.estimators.UnivariateQuantileEstimator

Returns the quantile for the given percentage

prefix() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns tree in prefix order.

prefix() - Method in class weka.classifiers.trees.J48

Returns tree in prefix order.

prefix() - Method in interface weka.core.Matchable

Returns a string that describes a tree representing the object in prefix order.

prepareRenderer(TableCellRenderer, int, int) - Method in class weka.gui.ETable

Shades alternate rows in different colors.

prePlot(Graphics) - Method in interface weka.gui.visualize.Plot2DCompanion

Something to be drawn before the plot itself

preProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.AveragingResultProducer

Prepare to generate results.

preProcess() - Method in class weka.experiment.CrossValidationResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener

Prepare for the results to be received.

preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener

Prepare for the results to be received.

preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.DatabaseResultProducer

Prepare to generate results.

preProcess() - Method in class weka.experiment.ExplicitTestsetResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener

Prepare for the results to be received.

preProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.LearningRateResultProducer

Prepare to generate results.

preProcess() - Method in class weka.experiment.RandomSplitResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in interface weka.experiment.ResultListener

Prepare for the results to be received.

preProcess() - Method in interface weka.experiment.ResultProducer

Prepare to generate results.

preprocessingTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter

Returns the tip text for this property

PreprocessPanel - Class in weka.gui.explorer

This panel controls simple preprocessing of instances.

PreprocessPanel() - Constructor for class weka.gui.explorer.PreprocessPanel

Creates the instances panel with no initial instances.

preserveInstancesOrderTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property.

PrincipalComponents - Class in weka.attributeSelection

Performs a principal components analysis and transformation of the data.

PrincipalComponents() - Constructor for class weka.attributeSelection.PrincipalComponents

PrincipalComponents - Class in weka.filters.unsupervised.attribute

Performs a principal components analysis and transformation of the data.
Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%).
Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger.

PrincipalComponents() - Constructor for class weka.filters.unsupervised.attribute.PrincipalComponents

print() - Method in class weka.classifiers.bayes.net.ADNode

print is used for debugging only and shows the ADTree in ASCII graphics

print(String) - Method in class weka.classifiers.bayes.net.VaryNode

print is used for debugging only, called from ADNode

print(Classifier, ConverterUtils.DataSource) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the header, classifications and footer to the buffer.

print(Classifier, Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the header, classifications and footer to the buffer.

print(int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given int to the streams.

print(boolean) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given boolean to the streams.

print(String) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given string to the streams.

print(Object) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given object to the streams.

print(int, int) - Method in class weka.core.matrix.Matrix

Print the matrix to stdout.

print(PrintWriter, int, int) - Method in class weka.core.matrix.Matrix

Print the matrix to the output stream.

print(NumberFormat, int) - Method in class weka.core.matrix.Matrix

Print the matrix to stdout.

print(PrintWriter, NumberFormat, int) - Method in class weka.core.matrix.Matrix

Print the matrix to the output stream.

print(int) - Method in class weka.core.Tee

prints the given int to the streams.

print(long) - Method in class weka.core.Tee

prints the given long to the streams.

print(float) - Method in class weka.core.Tee

prints the given float to the streams.

print(double) - Method in class weka.core.Tee

prints the given double to the streams.

print(boolean) - Method in class weka.core.Tee

prints the given boolean to the streams.

print(char) - Method in class weka.core.Tee

prints the given char to the streams.

print(char[]) - Method in class weka.core.Tee

prints the given char array to the streams.

print(String) - Method in class weka.core.Tee

prints the given string to the streams.

print(Object) - Method in class weka.core.Tee

prints the given object to the streams.

print() - Method in class weka.core.xml.XMLDocument

prints the current DOM document to standard out.

print(Graphics, PageFormat, int) - Method in class weka.gui.DocumentPrinting

Prints the page.

print(JTextPane) - Method in class weka.gui.DocumentPrinting

Prints the document in the JTextPane.

print_hash_code() - Method in class weka.classifiers.rules.DecisionTableHashKey

Prints the hash code

PrintableComponent - Class in weka.gui.visualize

This class extends the component which is handed over in the constructor by a print dialog.

PrintableComponent(JComponent) - Constructor for class weka.gui.visualize.PrintableComponent

initializes the panel.

PrintableHandler - Interface in weka.gui.visualize

This interface is for all JComponent classes that provide the ability to print itself to a file.

PrintablePanel - Class in weka.gui.visualize

This Panel enables the user to print the panel to various file formats.

PrintablePanel() - Constructor for class weka.gui.visualize.PrintablePanel

initializes the panel

printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode

Print all the linear models at the learf (debugging purposes)

printCanopyAssignments(Instances, List<long[]>) - Static method in class weka.clusterers.Canopy

Print the supplied instances and their canopies

printClassification(Classifier, Instance, int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the classification to the buffer.

printClassification(double[], Instance, int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the classification to the buffer.

printClassifications(Classifier, ConverterUtils.DataSource) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the classifications to the buffer.

printClassifications(Classifier, Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the classifications to the buffer.

printColNamesTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

printDialog() - Method in class weka.gui.DocumentPrinting

Shows the print dialog.

printElements() - Method in class weka.classifiers.functions.supportVector.SMOset

Prints all the current elements in the set.

printFeatures() - Method in class weka.classifiers.rules.DecisionTable

Returns a string description of the features selected

printFooter() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the footer to the buffer.

printHeader() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Prints the header to the buffer.

printInsts(int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

For printing indices in some given portion of the master index array.

printLeafModels() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree

Print the models at the leaves

printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode

print all leaf models

printLeafModelsTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

printList(MiddleOutConstructor.MyIdxList) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

For printing indices in a given point list.

println() - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints a new line to the streams.

println(int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given int to the streams.

println(boolean) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given boolean to the streams.

println(String) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given string to the streams.

println(Object) - Method in class weka.core.logging.OutputLogger.OutputPrintStream

prints the given object to the streams (for Throwables we print the stack trace).

println() - Method in class weka.core.Tee

prints a new line to the streams.

println(int) - Method in class weka.core.Tee

prints the given int to the streams.

println(long) - Method in class weka.core.Tee

prints the given long to the streams.

println(float) - Method in class weka.core.Tee

prints the given float to the streams.

println(double) - Method in class weka.core.Tee

prints the given double to the streams.

println(boolean) - Method in class weka.core.Tee

prints the given boolean to the streams.

println(char) - Method in class weka.core.Tee

prints the given char to the streams.

println(char[]) - Method in class weka.core.Tee

prints the given char array to the streams.

println(String) - Method in class weka.core.Tee

prints the given string to the streams.

println(Object) - Method in class weka.core.Tee

prints the given object to the streams (for Throwables we print the stack trace).

printNewickTipText() - Method in class weka.clusterers.HierarchicalClusterer

printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode

print the linear model at this node

printRowNamesTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

printSingleAssignment(long[]) - Static method in class weka.clusterers.Canopy

printStackTrace() - Method in class weka.core.Debug.Random

prints the current stacktrace

printTreesTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

priorEntropy() - Method in class weka.classifiers.evaluation.Evaluation

Calculate the entropy of the prior distribution.

priorEntropy() - Method in class weka.classifiers.Evaluation

Calculate the entropy of the prior distribution.

prnts - Variable in class weka.gui.graphvisualizer.GraphNode

The indices of parent nodes

prob(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class over all bags.

prob(int, int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class for given bag.

PROB_COST_FUNC_NAME - Static variable in class weka.classifiers.evaluation.CostCurve

attribute name: Probability Cost Function

probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats

Return the probability of an attribute value conditioned on a class value

probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats

probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats

probRound(double, Random) - Static method in class weka.core.Utils

Rounds a double to the next nearest integer value in a probabilistic fashion (e.g.

probs - Variable in class weka.gui.graphvisualizer.GraphNode

probability table for each outcome given outcomes of parents, if any

probToLogOdds(double) - Static method in class weka.core.Utils

Returns the log-odds for a given probabilitiy.

process(boolean[][], BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator

process(Instances) - Method in class weka.core.CheckScheme.PostProcessor

Provides a hook for derived classes to further modify the data.

process(Instances, double[][], Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

process(Instance, Classifier, Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info.

processChangedLines(int, int) - Method in class weka.gui.scripting.SyntaxDocument

Determine how many lines have been changed, then apply highlighting to each line.

processColour(String, Color) - Static method in class weka.gui.visualize.VisualizeUtils

Parses a string containing either a named colour or r,g,b values.

processFile(String) - Method in class weka.classifiers.bayes.net.BIFReader

processFile reads a BIFXML file and initializes a Bayes Net

processFilename(String) - Method in class weka.gui.Loader

returns the processed filename, i.e.

processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.CostBenefitAnalysis

Process a list of events that have been collected earlier.

processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.DataVisualizer

Process a list of events that have been collected earlier.

processHeadlessEvents(List<EventObject>) - Method in interface weka.gui.beans.HeadlessEventCollector

Process a list of events that have been collected earlier.

processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.ModelPerformanceChart

Process a list of events that have been collected earlier.

processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.TextViewer

Process a list of events that have been collected earlier.

PROCESSING - Static variable in class weka.experiment.TaskStatusInfo

processKeyString(String) - Static method in class weka.experiment.DatabaseUtils

processes the string in such a way that it can be stored in the database, i.e., it changes backslashes into slashes and doubles single quotes.

processString(String) - Method in class weka.classifiers.bayes.net.BIFReader

PRODUCT_RULE - Static variable in class weka.classifiers.meta.Vote

combination rule: Product of Probabilities (only nominal classes)

production_table() - Method in class weka.core.json.Parser

Access to production table.

production_table() - Method in class weka.core.mathematicalexpression.Parser

Access to production table.

production_table() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Access to production table.

PROPERTIES_DIR - Static variable in class weka.core.WekaPackageManager

The default properties directory

PROPERTIES_FILE - Static variable in class weka.core.Capabilities

the properties file for managing the tests

PROPERTIES_FILE - Static variable in class weka.core.logging.Logger

the properties file.

PROPERTIES_FILE - Static variable in class weka.gui.scripting.GroovyPanel

the Groovy setup.

PROPERTIES_FILE - Static variable in class weka.gui.scripting.JythonPanel

the Groovy setup.

PROPERTIES_FILE - Static variable in class weka.gui.treevisualizer.TreeVisualizer

the props file.

property - Variable in class weka.experiment.PropertyNode

Other info about the property

PROPERTY_FILE - Static variable in class weka.core.Copyright

the copyright file

PROPERTY_FILE - Static variable in class weka.experiment.DatabaseUtils

The name of the properties file.

PROPERTY_FILE - Static variable in class weka.gui.experiment.ExperimenterDefaults

The name of the properties file.

PROPERTY_FILE - Static variable in class weka.gui.explorer.ExplorerDefaults

The name of the properties file.

PROPERTY_FILE - Static variable in class weka.gui.LookAndFeel

The name of the properties file

propertyChange(PropertyChangeEvent) - Method in class weka.gui.beans.KnowledgeFlowApp

Accept property change events

propertyChange(PropertyChangeEvent) - Method in class weka.gui.PropertySheetPanel

Updates the property sheet panel with a changed property and also passed the event along.

PropertyDialog - Class in weka.gui

Support for PropertyEditors with custom editors: puts the editor into a separate frame.

PropertyDialog(PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog

Deprecated. instead of this constructor, one should use the constructors with an explicit owner (either derived from java.awt.Dialog or from java.awt.Frame) or, if none available, using (Frame) null as owner.

PropertyDialog(Dialog, PropertyEditor) - Constructor for class weka.gui.PropertyDialog

Creates the (screen-centered) editor dialog.

PropertyDialog(Dialog, PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog

Creates the editor dialog at the given position.

PropertyDialog(Frame, PropertyEditor) - Constructor for class weka.gui.PropertyDialog

Creates the (screen-centered) editor dialog.

PropertyDialog(Frame, PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog

Creates the editor dialog at the given position.

PropertyHandler - Class in weka.core.xml

This class stores information about properties to ignore or properties that are allowed for a certain class.

PropertyHandler() - Constructor for class weka.core.xml.PropertyHandler

initializes the handling

PropertyNode - Class in weka.experiment

Stores information on a property of an object: the class of the object with the property; the property descriptor, and the current value.

PropertyNode(Object) - Constructor for class weka.experiment.PropertyNode

Creates a mostly empty property.

PropertyNode(Object, PropertyDescriptor, Class<?>) - Constructor for class weka.experiment.PropertyNode

Creates a fully specified property node.

PropertyPanel - Class in weka.gui

Support for drawing a property value in a component.

PropertyPanel(PropertyEditor) - Constructor for class weka.gui.PropertyPanel

Create the panel with the supplied property editor.

PropertyPanel(PropertyEditor, boolean) - Constructor for class weka.gui.PropertyPanel

Create the panel with the supplied property editor, optionally ignoring any custom panel the editor can provide.

PropertyPath - Class in weka.core

A helper class for accessing properties in nested objects, e.g., accessing the "getRidge" method of a LinearRegression classifier part of MultipleClassifierCombiner, e.g., Vote.

PropertyPath() - Constructor for class weka.core.PropertyPath

PropertyPath.Path - Class in weka.core

Contains a (property) path structure

PropertyPath.Path(String) - Constructor for class weka.core.PropertyPath.Path

uses the given dot-path

PropertyPath.Path(Vector<PropertyPath.PathElement>) - Constructor for class weka.core.PropertyPath.Path

uses the vector with PathElement objects to initialize with

PropertyPath.Path(String[]) - Constructor for class weka.core.PropertyPath.Path

uses the given array as elements for the path

PropertyPath.PathElement - Class in weka.core

Represents a single element of a property path

PropertyPath.PathElement(String) - Constructor for class weka.core.PropertyPath.PathElement

initializes the path element with the given property

PropertySelectorDialog - Class in weka.gui

Allows the user to select any (supported) property of an object, including properties that any of it's property values may have.

PropertySelectorDialog(Frame, Object) - Constructor for class weka.gui.PropertySelectorDialog

Create the property selection dialog.

PropertySheetPanel - Class in weka.gui

Displays a property sheet where (supported) properties of the target object may be edited.

PropertySheetPanel() - Constructor for class weka.gui.PropertySheetPanel

Creates the property sheet panel.

ProtectedProperties - Class in weka.core

Simple class that extends the Properties class so that the properties are unable to be modified.

ProtectedProperties(Properties) - Constructor for class weka.core.ProtectedProperties

Creates a set of protected properties from a set of normal ones.

prune(Instances, boolean) - Method in class weka.classifiers.rules.JRip.RipperRule

Prune all the possible final sequences of the rule using the pruning data.

prune() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree

Prunes a tree using C4.5's pruning procedure.

prune() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree

Prunes a tree.

prune(double) - Method in class weka.classifiers.trees.lmt.LMTNode

Prunes a logistic model tree using the CART pruning scheme, given a cost-complexity parameter alpha.

prune(double[], double[], Instances) - Method in class weka.classifiers.trees.lmt.LMTNode

Method for performing one fold in the cross-validation of the cost-complexity parameter.

prune() - Method in class weka.classifiers.trees.m5.RuleNode

Recursively prune the tree

PruneableClassifierTree - Class in weka.classifiers.trees.j48

Class for handling a tree structure that can be pruned using a pruning set.

PruneableClassifierTree(ModelSelection, boolean, int, boolean, int) - Constructor for class weka.classifiers.trees.j48.PruneableClassifierTree

Constructor for pruneable tree structure.

PruneableDecList - Class in weka.classifiers.rules.part

Class for handling a partial tree structure that can be pruned using a pruning set.

PruneableDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.PruneableDecList

Constructor for pruneable partial tree structure.

pruneItemSets(ArrayList<Object>, Hashtable<ItemSet, Integer>) - Static method in class weka.associations.ItemSet

Prunes a set of (k)-item sets using the given (k-1)-item sets.

pruneItemSets(ArrayList<Object>, Hashtable<ItemSet, Integer>) - Static method in class weka.associations.LabeledItemSet

Prunes a set of (k)-item sets using the given (k-1)-item sets.

pruneRules(List<AssociationRule>, ArrayList<Item>, boolean) - Static method in class weka.associations.FPGrowth

pruneRules(ArrayList<Object>[], double) - Static method in class weka.associations.ItemSet

Prunes a set of rules.

pruneToK(Instances, double[], int) - Method in class weka.classifiers.lazy.IBk

Prunes the list to contain the k nearest neighbors.

PRUNING_LAMBDA - Static variable in class weka.classifiers.functions.supportVector.StringKernel

Pruning method: Lambda See [2] for details.

PRUNING_NONE - Static variable in class weka.classifiers.functions.supportVector.StringKernel

Pruning method: No Pruning

pruningMethodTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the tip text for this property

PSI - Static variable in class weka.core.matrix.Maths

The constant 1 / sqrt(2 pi)

Puk - Class in weka.classifiers.functions.supportVector

The Pearson VII function-based universal kernel.

For more information see:

B.

Puk() - Constructor for class weka.classifiers.functions.supportVector.Puk

default constructor - does nothing.

Puk(Instances, int, double, double) - Constructor for class weka.classifiers.functions.supportVector.Puk

Constructor.

PURE_INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is a pure input unit.

PURE_OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is a pure output unit.

push(T) - Method in class weka.core.neighboursearch.covertrees.Stack

Pushes the given element to the stack.

push(Stack<T>, T) - Method in class weka.core.neighboursearch.covertrees.Stack

Pushes the given element onto the given stack.

push(Object) - Method in class weka.core.Queue

Appends an object to the back of the queue.

pushParameterDefs() - Method in class weka.core.pmml.DefineFunction

put(Object, Object) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

putAll(Map<? extends Object, ? extends Object>) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

putResultInTable(String, ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseUtils

Executes a database query to insert a result for the supplied key into the database.

Q

qr() - Method in class weka.core.matrix.Matrix: QR Decomposition
QRDecomposition - Class in weka.core.matrix: QR Decomposition.
QRDecomposition(Matrix) - Constructor for class weka.core.matrix.QRDecomposition: QR Decomposition, computed by Householder reflections.
Quantile - Class in weka.core.pmml.jaxbbindings: Java class for Quantile element declaration.
Quantile() - Constructor for class weka.core.pmml.jaxbbindings.Quantile
queryExecuted(QueryExecuteEvent) - Method in interface weka.gui.sql.event.QueryExecuteListener: This method gets called when a query has been executed.
queryExecuted(QueryExecuteEvent) - Method in class weka.gui.sql.ResultPanel: This method gets called when a query has been executed.
queryExecuted(QueryExecuteEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when a query has been executed.
QueryExecuteEvent - Class in weka.gui.sql.event: An event that is generated when a query is executed.
QueryExecuteEvent(Object, DbUtils, String, int, ResultSet, Exception) - Constructor for class weka.gui.sql.event.QueryExecuteEvent: constructs the event
QueryExecuteListener - Interface in weka.gui.sql.event: A listener for executing queries.
QueryPanel - Class in weka.gui.sql: Represents a panel for entering an SQL query.
QueryPanel(JFrame) - Constructor for class weka.gui.sql.QueryPanel: initializes the panel.
queryTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
queryTipText() - Method in class weka.experiment.InstanceQuery: Returns the tip text for this property
Queue - Class in weka.core: Class representing a FIFO queue.
Queue() - Constructor for class weka.core.Queue
quickSort(double[], double[], int, int) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch: performs quicksort.
quote(String) - Static method in class weka.core.Utils: Quotes a string if it contains special characters.

R

R_MAX - Static variable in class weka.core.NormalizableDistance

Index in ranges for MAX.

R_MIN - Static variable in class weka.core.NormalizableDistance

Index in ranges for MIN.

R_WIDTH - Static variable in class weka.core.NormalizableDistance

Index in ranges for WIDTH.

RadialBasisKernelType - Class in weka.core.pmml.jaxbbindings

Java class for RadialBasisKernelType element declaration.

RadialBasisKernelType() - Constructor for class weka.core.pmml.jaxbbindings.RadialBasisKernelType

randEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper

used/reused to hold the random entropy

RANDOM - Static variable in class weka.clusterers.SimpleKMeans

random(int) - Static method in class weka.core.matrix.DoubleVector

Returns a random vector of uniform distribution

random(int, int) - Static method in class weka.core.matrix.Matrix

Generate matrix with random elements

RANDOM - Static variable in class weka.datagenerators.clusterers.BIRCHCluster

Constant set for choice of pattern.

RANDOM - Static variable in class weka.filters.supervised.attribute.ClassOrder

The class values are sorted in random order

RandomCommittee - Class in weka.classifiers.meta

Class for building an ensemble of randomizable base classifiers.

RandomCommittee() - Constructor for class weka.classifiers.meta.RandomCommittee

Constructor.

RandomForest - Class in weka.classifiers.trees

Class for constructing a forest of random trees.

For more information see:

Leo Breiman (2001).

RandomForest() - Constructor for class weka.classifiers.trees.RandomForest

Randomizable - Interface in weka.core

Interface to something that has random behaviour that is able to be seeded with an integer.

RandomizableClassifier - Class in weka.classifiers

Abstract utility class for handling settings common to randomizable classifiers.

RandomizableClassifier() - Constructor for class weka.classifiers.RandomizableClassifier

RandomizableClusterer - Class in weka.clusterers

Abstract utility class for handling settings common to randomizable clusterers.

RandomizableClusterer() - Constructor for class weka.clusterers.RandomizableClusterer

RandomizableDensityBasedClusterer - Class in weka.clusterers

Abstract utility class for handling settings common to randomizable clusterers.

RandomizableDensityBasedClusterer() - Constructor for class weka.clusterers.RandomizableDensityBasedClusterer

RandomizableFilteredClassifier - Class in weka.classifiers.meta

Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.

RandomizableFilteredClassifier() - Constructor for class weka.classifiers.meta.RandomizableFilteredClassifier

Default constructor.

RandomizableIteratedSingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.

RandomizableIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

RandomizableMultipleClassifiersCombiner - Class in weka.classifiers

Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.

RandomizableMultipleClassifiersCombiner() - Constructor for class weka.classifiers.RandomizableMultipleClassifiersCombiner

RandomizableParallelIteratedSingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.

RandomizableParallelIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

RandomizableParallelMultipleClassifiersCombiner - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers based on a given random number seed.

RandomizableParallelMultipleClassifiersCombiner() - Constructor for class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

RandomizableSingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.

RandomizableSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableSingleClassifierEnhancer

RandomizableSingleClustererEnhancer - Class in weka.clusterers

Abstract utility class for handling settings common to randomizable clusterers.

RandomizableSingleClustererEnhancer() - Constructor for class weka.clusterers.RandomizableSingleClustererEnhancer

randomize(int[], Random) - Method in class weka.classifiers.BVDecomposeSegCVSub

Accepts an array of ints and randomises the values in the array, using the random seed.

randomize(Random) - Method in class weka.core.Instances

Shuffles the instances in the set so that they are ordered randomly.

Randomize - Class in weka.filters.unsupervised.instance

Randomly shuffles the order of instances passed through it.

Randomize() - Constructor for class weka.filters.unsupervised.instance.Randomize

RANDOMIZED - Static variable in class weka.datagenerators.clusterers.BIRCHCluster

Constant set for input order (default)

randomizeDataTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

randomizeDataTipText() - Method in class weka.experiment.RandomSplitResultProducer

Returns the tip text for this property

RandomLiftGraph - Class in weka.core.pmml.jaxbbindings

Java class for RandomLiftGraph element declaration.

RandomLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.RandomLiftGraph

randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.global.K2

randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.local.K2

RandomProjection - Class in weka.filters.unsupervised.attribute

Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (i.e.

RandomProjection() - Constructor for class weka.filters.unsupervised.attribute.RandomProjection

RandomRBF - Class in weka.datagenerators.classifiers.classification

RandomRBF data is generated by first creating a random set of centers for each class.

RandomRBF() - Constructor for class weka.datagenerators.classifiers.classification.RandomRBF

initializes the generator with default values

randomSeedTipText() - Method in class weka.classifiers.functions.SMO

Returns the tip text for this property

randomSeedTipText() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Returns the tip text for this property.

randomSeedTipText() - Method in class weka.filters.supervised.instance.Resample

Returns the tip text for this property.

randomSeedTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample

Returns the tip text for this property

randomSeedTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Randomize

Returns the tip text for this property

randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Resample

Returns the tip text for this property

randomSeedTipText() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns the tip text for this property

RandomSplitResultProducer - Class in weka.experiment

Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.

RandomSplitResultProducer() - Constructor for class weka.experiment.RandomSplitResultProducer

RandomSubset - Class in weka.filters.unsupervised.attribute

Chooses a random subset of attributes, either an absolute number or a percentage.

RandomSubset() - Constructor for class weka.filters.unsupervised.attribute.RandomSubset

RandomSubSpace - Class in weka.classifiers.meta

This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity.

RandomSubSpace() - Constructor for class weka.classifiers.meta.RandomSubSpace

Constructor.

randomTipText() - Method in class weka.datagenerators.DataGenerator

Returns the tip text for this property

RandomTree - Class in weka.classifiers.trees

Class for constructing a tree that considers K randomly chosen attributes at each node.

RandomTree() - Constructor for class weka.classifiers.trees.RandomTree

RandomVariates - Class in weka.core

Class implementing some simple random variates generator.

RandomVariates() - Constructor for class weka.core.RandomVariates

Simply the constructor of super class

RandomVariates(long) - Constructor for class weka.core.RandomVariates

Simply the constructor of super class

randomWidthFactorTipText() - Method in class weka.classifiers.meta.MultiClassClassifier

Range - Class in weka.core

Class representing a range of cardinal numbers.

Range() - Constructor for class weka.core.Range

Default constructor.

Range(String) - Constructor for class weka.core.Range

Constructor to set initial range.

rangesSet() - Method in class weka.core.NormalizableDistance

Check if ranges are set.

rangesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Returns the tip text for this property.

rank() - Method in class weka.core.matrix.Matrix

Matrix rank

rank() - Method in class weka.core.matrix.SingularValueDecomposition

Effective numerical matrix rank

rankedAttributes() - Method in class weka.attributeSelection.AttributeSelection

get the final ranking of the attributes.

rankedAttributes() - Method in class weka.attributeSelection.GreedyStepwise

Produces a ranked list of attributes.

rankedAttributes() - Method in interface weka.attributeSelection.RankedOutputSearch

Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.

rankedAttributes() - Method in class weka.attributeSelection.Ranker

Sorts the evaluated attribute list

RankedOutputSearch - Interface in weka.attributeSelection

Interface for search methods capable of producing a ranked list of attributes.

Ranker - Class in weka.attributeSelection

Ranker :

Ranks attributes by their individual evaluations.

Ranker() - Constructor for class weka.attributeSelection.Ranker

Constructor

rawOutputTipText() - Method in class weka.experiment.CrossValidationResultProducer

Returns the tip text for this property

rawOutputTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

rawOutputTipText() - Method in class weka.experiment.RandomSplitResultProducer

Returns the tip text for this property

RBFKernel - Class in weka.classifiers.functions.supportVector

The RBF kernel.

RBFKernel() - Constructor for class weka.classifiers.functions.supportVector.RBFKernel

default constructor - does nothing.

RBFKernel(Instances, int, double) - Constructor for class weka.classifiers.functions.supportVector.RBFKernel

Constructor.

rchisq(int, double, Random) - Static method in class weka.core.matrix.Maths

Generates a sample of a Chi-square distribution.

RCURLY - Static variable in interface weka.core.json.sym

RDG1 - Class in weka.datagenerators.classifiers.classification

A data generator that produces data randomly by producing a decision list.
The decision list consists of rules.
Instances are generated randomly one by one.

RDG1() - Constructor for class weka.datagenerators.classifiers.classification.RDG1

initializes the generator with default values

read(String) - Static method in class weka.core.converters.ConverterUtils.DataSource

convencience method for loading a dataset in batch mode.

read(InputStream) - Static method in class weka.core.converters.ConverterUtils.DataSource

convencience method for loading a dataset in batch mode from a stream.

read(Loader) - Static method in class weka.core.converters.ConverterUtils.DataSource

convencience method for loading a dataset in batch mode.

read(Reader) - Static method in class weka.core.json.JSONNode

Reads the JSON object from the given reader.

read(BufferedReader) - Static method in class weka.core.matrix.Matrix

Read a matrix from a stream.

read(String) - Static method in class weka.core.SerializationHelper

deserializes the given file and returns the object from it.

read(InputStream) - Static method in class weka.core.SerializationHelper

deserializes from the given stream and returns the object from it.

read(String) - Method in class weka.core.Stopwords

Generates a new Stopwords object from the given file

read(File) - Method in class weka.core.Stopwords

Generates a new Stopwords object from the given file

read(BufferedReader) - Method in class weka.core.Stopwords

Generates a new Stopwords object from the reader.

read(String) - Static method in class weka.core.xml.KOML

reads the XML-serialized object from the given file

read(File) - Static method in class weka.core.xml.KOML

reads the XML-serialized object from the given file

read(InputStream) - Static method in class weka.core.xml.KOML

reads the XML-serialized object from a stream

read(String) - Method in class weka.core.xml.XMLDocument

parses the given XML string (can be XML or a filename) and returns a DOM Document.

read(File) - Method in class weka.core.xml.XMLDocument

parses the given file and returns a DOM document.

read(InputStream) - Method in class weka.core.xml.XMLDocument

parses the given stream and returns a DOM document.

read(Reader) - Method in class weka.core.xml.XMLDocument

parses the given reader and returns a DOM document.

read(String) - Method in class weka.core.xml.XMLSerialization

parses the given XML string (can be XML or a filename) and returns an Object generated from the representation

read(File) - Method in class weka.core.xml.XMLSerialization

parses the given file and returns a DOM document

read(InputStream) - Method in class weka.core.xml.XMLSerialization

parses the given stream and returns a DOM document

read(Reader) - Method in class weka.core.xml.XMLSerialization

parses the given reader and returns a DOM document

read() - Method in class weka.core.xml.XMLSerializationMethodHandler

returns the handler for read methods

read(String) - Static method in class weka.core.xml.XStream

reads the XML-serialized object from the given file

read(File) - Static method in class weka.core.xml.XStream

reads the XML-serialized object from the given file

read(InputStream) - Static method in class weka.core.xml.XStream

reads the XML-serialized object from the given input stream

read(Reader) - Static method in class weka.core.xml.XStream

reads the XML-serialized object from the given Reader

read(String) - Static method in class weka.experiment.Experiment

Loads an experiment from a file.

readAll(String) - Static method in class weka.core.SerializationHelper

deserializes the given file and returns the objects from it.

readAll(InputStream) - Static method in class weka.core.SerializationHelper

deserializes from the given stream and returns the object from it.

readBeanConnection(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the BeanConnection from the given DOM node.

readBeanInstance(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the BeanInstance from the given DOM node.

readBeanVisual(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the BeanVisual from the given DOM node.

readBIF(String) - Method in class weka.gui.graphvisualizer.GraphVisualizer

BIF reader
Reads a graph description in XMLBIF03 from a string

readBIF(InputStream) - Method in class weka.gui.graphvisualizer.GraphVisualizer

BIF reader
Reads a graph description in XMLBIF03 from an InputStrem

readBIFFromFile(String) - Method in class weka.classifiers.bayes.net.GUI

BIF reader
Reads a graph description in XMLBIF03 from an file with name sFileName

readBooleanFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readByteFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readCharFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readCollection(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the Collection from the given DOM node.

readColor(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Color from the given DOM node.

readColorUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the ColorUIResource from the given DOM node.

readCostMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the Matrix (old) from the given DOM node.

readDefaultListModel(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the DefaultListModel from the given DOM node.

readDimension(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Dimension from the given DOM node.

readDOT(Reader) - Method in class weka.gui.graphvisualizer.GraphVisualizer

Dot reader
Reads a graph description in DOT format from a string

readDoubleFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

ReaderToTextPane - Class in weka.gui

A class that sends all lines from a reader to a JTextPane component.

ReaderToTextPane(Reader, JTextPane) - Constructor for class weka.gui.ReaderToTextPane

Sets up the thread.

ReaderToTextPane(Reader, JTextPane, Color) - Constructor for class weka.gui.ReaderToTextPane

Sets up the thread.

readFloatFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readFont(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Font from the given DOM node.

readFontUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the FontUIResource from the given DOM node.

readFromXML(Object, String, Element) - Method in class weka.core.xml.XMLSerialization

adds the specific node to the object via a set method

readFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the object from the given DOM node.

readInstance(Instances) - Method in class weka.core.converters.ArffLoader.ArffReader

Reads a single instance using the tokenizer and returns it.

readInstance(Instances, boolean) - Method in class weka.core.converters.ArffLoader.ArffReader

Reads a single instance using the tokenizer and returns it.

readInstance(Reader) - Method in class weka.core.Instances

Deprecated. instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.

readIntFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readLoader(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Loader from the given DOM node.

readLongFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

readMap(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the Map from the given DOM node.

readMatrix(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the Matrix from the given DOM node.

readMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization

builds the Matrix (old) from the given DOM node.

readMetaBean(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the MetaBean from the given DOM node.

readOldFormat(Reader) - Method in class weka.classifiers.CostMatrix

Loads a cost matrix in the old format from a reader.

readPoint(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Point from the given DOM node.

readProperties(String) - Static method in class weka.core.Utils

Reads properties that inherit from three locations.

readPropertyNode(Element) - Method in class weka.experiment.xml.XMLExperiment

builds the PropertyNode from the given DOM node.

readSaver(Element) - Method in class weka.gui.beans.xml.XMLBeans

builds the Saver from the given DOM node.

readShortFromXML(Element) - Method in class weka.core.xml.XMLSerialization

builds the primitive from the given DOM node.

realCount - Variable in class weka.core.AttributeStats

The number of real-like values (i.e.

REALSparseArray - Class in weka.core.pmml.jaxbbindings

Java class for REAL-SparseArray element declaration.

REALSparseArray() - Constructor for class weka.core.pmml.jaxbbindings.REALSparseArray

recall(int) - Method in class weka.classifiers.evaluation.Evaluation

Calculate the recall with respect to a particular class.

recall(int) - Method in class weka.classifiers.Evaluation

Calculate the recall with respect to a particular class.

RECALL_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

attribute name: Recall

RECTANGLE - Static variable in class weka.gui.visualize.VisualizePanelEvent

redo() - Method in class weka.classifiers.bayes.net.EditableBayesNet

redo the last edit action performed on the network.

reduce_table() - Method in class weka.core.json.Parser

Access to reduce_goto table.

reduce_table() - Method in class weka.core.mathematicalexpression.Parser

Access to reduce_goto table.

reduce_table() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Access to reduce_goto table.

reducedErrorPruningTipText() - Method in class weka.classifiers.rules.PART

Returns the tip text for this property

reducedErrorPruningTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

reduceDimensionality(Instances) - Method in class weka.attributeSelection.AttributeSelection

reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.

reduceDimensionality(Instance) - Method in class weka.attributeSelection.AttributeSelection

reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.

reduceDL(double, boolean) - Method in class weka.classifiers.rules.RuleStats

Try to reduce the DL of the ruleset by testing removing the rules one by one in reverse order and update all the stats

reduceMatrix(double[][]) - Static method in class weka.core.ContingencyTables

Reduces a matrix by deleting all zero rows and columns.

reduceNumberOfDistanceCalcsViaCanopiesTipText() - Method in class weka.clusterers.SimpleKMeans

Returns the tip text for this property.

refresh() - Method in class weka.gui.arffviewer.ArffViewer

validates and repaints the frame

refresh() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

validates and repaints the frame

refreshCache(PrintStream...) - Static method in class weka.core.WekaPackageManager

Refresh the local copy of the package meta data

refreshFreqTipText() - Method in class weka.gui.beans.StripChart

GUI Tip text

refreshGOEProperties() - Static method in class weka.core.WekaPackageManager

Refresh the generic object editor properties via re-running of the dynamic class discovery process.

regenerateGlobalOutputProperties() - Static method in class weka.gui.GenericPropertiesCreator

Regenerate the global output properties.

REGEXP - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

register(Object, Class<?>, String) - Method in class weka.core.xml.XMLSerializationMethodHandler

adds read and write methods for the given class, i.e., read&;lt;name> and write<name> ("name" is prefixed by read and write)

registerEditor(String, String) - Static method in class weka.gui.GenericObjectEditor

registerEditors() - Static method in class weka.gui.GenericObjectEditor

registers all the editors in Weka.

RegOptimizer - Class in weka.classifiers.functions.supportVector

Base class implementation for learning algorithm of SMOreg Valid options are:

RegOptimizer() - Constructor for class weka.classifiers.functions.supportVector.RegOptimizer

the default constructor

regOptimizerTipText() - Method in class weka.classifiers.functions.SMOreg

Returns the tip text for this property

Regression - Class in weka.classifiers.pmml.consumer

Class implementing import of PMML Regression model.

Regression(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.Regression

Constructs a new PMML Regression.

regression(Matrix, double) - Method in class weka.core.matrix.Matrix

Performs a (ridged) linear regression.

regression(Matrix, double[], double) - Method in class weka.core.matrix.Matrix

Performs a weighted (ridged) linear regression.

regression(Matrix, double) - Method in class weka.core.Matrix

Deprecated. Performs a (ridged) linear regression.

regression(Matrix, double[], double) - Method in class weka.core.Matrix

Deprecated. Performs a weighted (ridged) linear regression.

Regression - Class in weka.core.pmml.jaxbbindings

Java class for Regression element declaration.

Regression() - Constructor for class weka.core.pmml.jaxbbindings.Regression

RegressionAnalysis - Class in weka.classifiers.evaluation

Analyzes linear regression model by using the Student's t-test on each coefficient.

RegressionAnalysis() - Constructor for class weka.classifiers.evaluation.RegressionAnalysis

RegressionByDiscretization - Class in weka.classifiers.meta

A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.

RegressionByDiscretization() - Constructor for class weka.classifiers.meta.RegressionByDiscretization

Default constructor.

RegressionGenerator - Class in weka.datagenerators

Abstract class for data generators for regression classifiers.

RegressionGenerator() - Constructor for class weka.datagenerators.RegressionGenerator

initializes the generator with default values

RegressionModel - Class in weka.core.pmml.jaxbbindings

Java class for RegressionModel element declaration.

RegressionModel() - Constructor for class weka.core.pmml.jaxbbindings.RegressionModel

REGRESSIONNORMALIZATIONMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for REGRESSIONNORMALIZATIONMETHOD.

RegressionSplitEvaluator - Class in weka.experiment

A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.

RegressionSplitEvaluator() - Constructor for class weka.experiment.RegressionSplitEvaluator

No args constructor.

RegressionTable - Class in weka.core.pmml.jaxbbindings

Java class for RegressionTable element declaration.

RegressionTable() - Constructor for class weka.core.pmml.jaxbbindings.RegressionTable

RegressionTable(String) - Constructor for class weka.core.pmml.jaxbbindings.RegressionTable

RegSMO - Class in weka.classifiers.functions.supportVector

Implementation of SMO for support vector regression as described in :

A.J.

RegSMO() - Constructor for class weka.classifiers.functions.supportVector.RegSMO

default constructor

RegSMOImproved - Class in weka.classifiers.functions.supportVector

Learn SVM for regression using SMO with Shevade, Keerthi, et al.

RegSMOImproved() - Constructor for class weka.classifiers.functions.supportVector.RegSMOImproved

reInitialize() - Static method in class weka.gui.beans.KnowledgeFlowApp

relation() - Method in class weka.core.Attribute

Returns the header info for a relation-valued attribute, null if the attribute is not relation-valued.

relation(int) - Method in class weka.core.Attribute

Returns a value of a relation-valued attribute.

RELATION - Static variable in class weka.core.json.JSONInstances

the relation name.

RELATION_NAME - Static variable in class weka.classifiers.evaluation.CostCurve

The name of the relation used in cost curve datasets

RELATION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

The name of the relation used in threshold curve datasets

RELATIONAL - Static variable in class weka.core.Attribute

Constant set for relation-valued attributes.

RelationalLocator - Class in weka.core

This class locates and records the indices of relational attributes,

RelationalLocator(Instances) - Constructor for class weka.core.RelationalLocator

Initializes the RelationalLocator with the given data.

RelationalLocator(Instances, int, int) - Constructor for class weka.core.RelationalLocator

Initializes the RelationalLocator with the given data.

RelationalLocator(Instances, int[]) - Constructor for class weka.core.RelationalLocator

Initializes the RelationalLocator with the given data.

relationalValue(int) - Method in class weka.core.AbstractInstance

Returns the relational value of a relational attribute.

relationalValue(Attribute) - Method in class weka.core.AbstractInstance

Returns the relational value of a relational attribute.

relationalValue(int) - Method in interface weka.core.Instance

Returns the relational value of a relational attribute.

relationalValue(Attribute) - Method in interface weka.core.Instance

Returns the relational value of a relational attribute.

relationFindTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

relationForTableNameTipText() - Method in class weka.core.converters.DatabaseSaver

Returns the tip text fo this property.

relationName() - Method in class weka.core.Instances

Returns the relation's name.

relationNameTipText() - Method in class weka.datagenerators.DataGenerator

Returns the tip text for this property

relationReplaceTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

relativeAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the relative absolute error.

relativeAbsoluteError() - Method in class weka.classifiers.Evaluation

Returns the relative absolute error.

relativeDL(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats

The description length (DL) of the ruleset relative to if the rule in the given position is deleted, which is obtained by:
MDL if the rule exists - MDL if the rule does not exist
Note the minimal possible DL of the ruleset is calculated(i.e.

ReliefFAttributeEval - Class in weka.attributeSelection

ReliefFAttributeEval :

Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.

ReliefFAttributeEval() - Constructor for class weka.attributeSelection.ReliefFAttributeEval

Constructor

RemoteBoundaryVisualizerSubTask - Class in weka.gui.boundaryvisualizer

Class that encapsulates a sub task for distributed boundary visualization.

RemoteBoundaryVisualizerSubTask() - Constructor for class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

RemoteEngine - Class in weka.experiment

A general purpose server for executing Task objects sent via RMI.

RemoteEngine(String) - Constructor for class weka.experiment.RemoteEngine

Constructor

RemoteExperiment - Class in weka.experiment

Holds all the necessary configuration information for a distributed experiment.

RemoteExperiment() - Constructor for class weka.experiment.RemoteExperiment

Construct a new RemoteExperiment using an empty Experiment as base Experiment

RemoteExperiment(Experiment) - Constructor for class weka.experiment.RemoteExperiment

Construct a new RemoteExperiment using a base Experiment

RemoteExperimentEvent - Class in weka.experiment

Class encapsulating information on progress of a remote experiment

RemoteExperimentEvent(boolean, boolean, boolean, String) - Constructor for class weka.experiment.RemoteExperimentEvent

Constructor

RemoteExperimentListener - Interface in weka.experiment

Interface for classes that want to listen for updates on RemoteExperiment progress

remoteExperimentStatus(RemoteExperimentEvent) - Method in interface weka.experiment.RemoteExperimentListener

Called when progress has been made in a remote experiment

RemoteExperimentSubTask - Class in weka.experiment

Class to encapsulate an experiment as a task that can be executed on a remote host.

RemoteExperimentSubTask() - Constructor for class weka.experiment.RemoteExperimentSubTask

RemoteResult - Class in weka.gui.boundaryvisualizer

Class that encapsulates a result (and progress info) for part of a distributed boundary visualization.

RemoteResult(int, int) - Constructor for class weka.gui.boundaryvisualizer.RemoteResult

Creates a new RemoteResult instance.

remove(String) - Method in class weka.core.ClassCache

Removes the classname from the cache.

remove(int) - Method in class weka.core.Instances

Removes the instance at the given position.

remove(Object) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

remove(String) - Method in class weka.core.Stopwords

removes the word from the stopword list

remove(PrintStream) - Method in class weka.core.Tee

removes the given PrintStream from the list.

remove(int) - Method in class weka.core.Tee

removes the given PrintStream from the list.

remove(Object) - Method in class weka.core.Trie

Removes a single instance of the specified element from this collection, if it is present.

remove() - Method in class weka.core.Trie.TrieIterator

ignored

remove(String) - Method in class weka.core.Trie.TrieNode

Removes a suffix from the trie.

remove(String) - Method in class weka.core.xml.MethodHandler

removes the method for the property specified by the display name from its internal list.

remove(Class<?>) - Method in class weka.core.xml.MethodHandler

removes the method for the specified class from its internal list.

Remove - Class in weka.filters.unsupervised.attribute

An filter that removes a range of attributes from the dataset.

Remove() - Constructor for class weka.filters.unsupervised.attribute.Remove

Constructor so that we can initialize the Range variable properly.

remove(Integer...) - Method in class weka.gui.beans.BeanConnection

Remove this connection

remove(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Removes the element at the specified position in this list.

remove(int, int) - Method in class weka.gui.scripting.SyntaxDocument

Applies syntax highlighting after the document has been updated.

REMOVE_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

REMOVE_POINT_RADIUS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel

The distance we can click away from a point in the GUI and still remove it.

removeActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Remove a listener

removeAll(Collection<?>) - Method in class weka.core.Trie

Removes all this collection's elements that are also contained in the specified collection

removeAllBeansFromContainer(JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance

Removes all beans from containing component

removeAllElements() - Method in class weka.core.FastVector

Deprecated. Removes all components from this vector and sets its size to zero.

removeAllElements() - Method in class weka.core.Queue

Removes all objects from the queue m_Tail.m_Next.

removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

This function will remove all the inputs to this unit.

removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralNode

This function will remove all the inputs to this unit.

removeAllInstances() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Deletes all training instances from our dataset.

removeAllMissingColsTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

removeAllOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection

This function will remove all outputs to this unit.

removeAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler

removes the given property (display name) for the specified class from the list of allowed properties.

removeAllPlots() - Method in class weka.gui.visualize.Plot2D

Clears all plots

removeAllPlots() - Method in class weka.gui.visualize.VisualizePanel

Removes all the plots.

removeBatchAssociationRulesListener(BatchAssociationRulesListener) - Method in class weka.gui.beans.Associator

Remove a batch association rules listener

removeBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier

Remove a batch classifier listener

removeBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer

Remove a batch clusterer listener

removeBean(JComponent, Integer...) - Method in class weka.gui.beans.BeanInstance

Remove this bean from the list of beans and from the containing component

removeBeanInstances(JComponent, Integer) - Static method in class weka.gui.beans.BeanInstance

Remove the vector of bean instances from the supplied index in the list of collections.

RemoveByName - Class in weka.filters.unsupervised.attribute

Removes attributes based on a regular expression matched against their names.

RemoveByName() - Constructor for class weka.filters.unsupervised.attribute.RemoveByName

removeCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to remove an action listener from the cancel button.

removeCapabilitiesFilter() - Method in class weka.gui.GenericObjectEditor

Removes the current Capabilities filter.

removeCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer

Removes the specified listener from the set of listeners if it is present.

removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel

Removes a ChangeListener from the panel

removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable

Removes a ChangeListener from the panel

removeChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Remove a chart listener

removeChildFrame(Container) - Method in class weka.gui.GUIChooser

tries to remove the child frame, it returns true if it could do such.

removeChildFrame(Container) - Method in class weka.gui.Main

tries to remove the child frame, it returns true if it could do such.

removeClassColumnTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Returns the tip text for this property

removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator

We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).

removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier

We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).

removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer

We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).

removeConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer

We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).

removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter

We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).

removeConnectionList(Integer) - Static method in class weka.gui.beans.BeanConnection

Remove the list of connections at the supplied index

removeConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel

removes the given listener from the list of listeners.

removeConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer

removes the given listener from the list of listeners.

removeConnections(BeanInstance, Integer...) - Static method in class weka.gui.beans.BeanConnection

Remove all connections for a bean.

removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner

removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource

Remove a listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Appender

Remove a data source listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker

removeDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource

Remove a data source listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer

Remove a listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter

Remove a data source listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.FlowByExpression

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Join

Remove a data souce listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader

Remove a listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender

Remove a datasource listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Sorter

Remove a datasource listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringLabeler

Remove a datasource listener

removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringReplacer

Remove a data source listener

RemoveDuplicates - Class in weka.filters.unsupervised.instance

Removes all duplicate instances from the first batch of data it receives.

RemoveDuplicates() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicates

removeElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Removes the first (lowest-indexed) occurrence of the argument from this list.

removeElementAt(int) - Method in class weka.core.FastVector

Deprecated. Deletes an element from this vector.

removeExplorerProps(String) - Static method in class weka.core.WekaPackageManager

Remove any ExplorerDefaults properties specified in the supplied package

removeFilterNameTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

RemoveFolds - Class in weka.filters.unsupervised.instance

This filter takes a dataset and outputs a specified fold for cross validation.

RemoveFolds() - Constructor for class weka.filters.unsupervised.instance.RemoveFolds

RemoveFrequentValues - Class in weka.filters.unsupervised.instance

Determines which values (frequent or infrequent ones) of an (nominal) attribute are retained and filters the instances accordingly.

RemoveFrequentValues() - Constructor for class weka.filters.unsupervised.instance.RemoveFrequentValues

removeFromDisabledList(List<String>) - Static method in class weka.gui.beans.PluginManager

Remove the supplied list of fully qualified class names to the disabled list

removeFromDisabledList(String) - Static method in class weka.gui.beans.PluginManager

Remove the supplied fully qualified class name from the list of disabled plugins

removeFromPluginBeanProps(File) - Static method in class weka.gui.beans.BeansProperties

removeFromPluginBeanProps(File) - Static method in class weka.gui.beans.KnowledgeFlowApp

removeGraphListener(GraphListener) - Method in class weka.gui.beans.Associator

Remove a graph listener

removeGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier

Remove a graph listener

removeGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer

Remove a graph listener

removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel

removes the given listener from the list of listeners.

removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel

removes the given listener from the list of listeners.

removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer

removes the given listener from the list of listeners.

removeIgnored(String) - Method in class weka.core.xml.PropertyHandler

removes the given display name from the ignore list.

removeIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler

removes the given display name from the ignore list of the class.

removeImageListener(ImageListener) - Method in class weka.gui.beans.DataVisualizer

Remove an image listener

removeImageListener(ImageListener) - Method in class weka.gui.beans.ModelPerformanceChart

Remove an image listener

removeIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier

Remove an incremental classifier listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Appender

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner

removeInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.FlowByExpression

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Join

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Sorter

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringLabeler

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringReplacer

Remove an instance listener

removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner

removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader

removeInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer

removeKeyword(String) - Method in class weka.gui.scripting.SyntaxDocument

Removes an association between a keyword with a particular formatting style.

removeLast() - Method in class weka.classifiers.rules.RuleStats

Remove the last rule in the ruleset as well as it's stats.

removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

Method to remove a LayoutCompleteEventListener.

removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method removes a LayoutCompleteEventListener from the LayoutEngine.

removeLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2

removes an element (Link) at a specific index from the list.

RemoveMisclassified - Class in weka.filters.unsupervised.instance

A filter that removes instances which are incorrectly classified.

RemoveMisclassified() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassified

removeNotify() - Method in class weka.gui.beans.FileEnvironmentField

removeNotify() - Method in class weka.gui.PropertyPanel

Cleans up when the panel is destroyed.

removeOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to remove an action listener from the ok button.

removeOldClassTipText() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the tip text for this property.

RemovePercentage - Class in weka.filters.unsupervised.instance

A filter that removes a given percentage of a dataset.

RemovePercentage() - Constructor for class weka.filters.unsupervised.instance.RemovePercentage

removePlugin(String, String) - Static method in class weka.gui.beans.PluginManager

Remove a plugin.

removePlugins(String, List<String>) - Static method in class weka.gui.beans.PluginManager

Remove plugins of a specific type.

removePreBuiltClassifier(Classifier) - Method in class weka.classifiers.meta.Vote

Remove a prebuilt classifier from the list to use in the ensemble

removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource

Remove a property change listener from this bean

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

Remove a property change listener

removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer

Remove a property change listener from this bean

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.EnvironmentField

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer

Remove a property change listener

removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart

Remove a property change listener from this bean

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer

Remove a property change listener

removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer

Remove a property change listener from this bean

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor

Removes an object from the list of those that wish to be informed when the cost matrix changes.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor

Removes an object from the list of those that wish to be informed when the date format changes.

removePropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean

removeQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel

removes the given listener from the list of listeners.

removeQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer

removes the given listener from the list of listeners.

RemoveRange - Class in weka.filters.unsupervised.instance

A filter that removes a given range of instances of a dataset.

RemoveRange() - Constructor for class weka.filters.unsupervised.instance.RemoveRange

removeResult(String) - Method in class weka.gui.ResultHistoryPanel

Removes one of the result buffers from the history.

removeResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel

removes the given listener from the list of listeners

removeResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer

removes the given listener from the list of listeners.

removeScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script

Removes the given listener from its internal list.

removeSubstring(String, String) - Static method in class weka.core.Utils

Removes all occurrences of a string from another string.

removeTab(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel

removes a listener from the list that is notified each time a change to the data model occurs

removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel

removes a listener from the list that is notified each time a change to the data model occurs

removeTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel

removes a listener from the list that is notified each time a change to the data model occurs.

removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer

Remove a listener for test sets

removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Remove a test set listener

removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner

removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter

Remove a test set listener

removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender

Remove a test set listener

removeTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer

Remove a listener for test set events

removeTextListener(TextListener) - Method in class weka.gui.beans.Associator

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.Classifier

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.Clusterer

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Remove a text listener

removeTextListener(TextListener) - Method in class weka.gui.beans.TextViewer

Remove a text listener

removeThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Remove a Threshold data listener

removeTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel

Removes the listener from the internal list.

removeTrainingInstanceFromMouseLocation(int, int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Removes a single training instance from our dataset, if there is one that is close enough to the specified mouse location.

removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Remove a training set listener

removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer

Remove a training set listener

removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner

removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter

Remove a training set listener

removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender

Remove a training set listener

removeTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer

Remove a training set listener

RemoveType - Class in weka.filters.unsupervised.attribute

Removes attributes of a given type.

RemoveType() - Constructor for class weka.filters.unsupervised.attribute.RemoveType

removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Returns the tip text for this property.

RemoveUseless - Class in weka.filters.unsupervised.attribute

This filter removes attributes that do not vary at all or that vary too much.

RemoveUseless() - Constructor for class weka.filters.unsupervised.attribute.RemoveUseless

removeVariable(String) - Method in class weka.core.Environment

Remove a named variable from the map.

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource

Remove a vetoable change listener from this bean

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.CostBenefitAnalysis

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer

Remove a vetoable change listener from this bean

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer

Remove a vetoable change listener from this bean

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart

Remove a vetoable change listener from this bean

removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer

Remove a vetoable change listener from this bean

removeVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Remove a visualizable error listener

RemoveWithValues - Class in weka.filters.unsupervised.instance

Filters instances according to the value of an attribute.

RemoveWithValues() - Constructor for class weka.filters.unsupervised.instance.RemoveWithValues

Default constructor

renameAttribute(int, String) - Method in class weka.core.Instances

Renames an attribute.

renameAttribute(Attribute, String) - Method in class weka.core.Instances

Renames an attribute.

RenameAttribute - Class in weka.filters.unsupervised.attribute

This filter is used for renaming attribute names.
Regular expressions can be used in the matching and replacing.
See Javadoc of java.util.regex.Pattern class for more information:
http://java.sun.com/javase/6/docs/api/java/util/regex/Pattern.html

Valid options are:

RenameAttribute() - Constructor for class weka.filters.unsupervised.attribute.RenameAttribute

renameAttribute() - Method in class weka.gui.arffviewer.ArffPanel

renames the current attribute

renameAttribute() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

renames the current selected Attribute

renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffSortedTableModel

renames the attribute at the given col index

renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffTableModel

renames the attribute at the given col index

renameAttributeValue(int, int, String) - Method in class weka.core.Instances

Renames the value of a nominal (or string) attribute value.

renameAttributeValue(Attribute, String, String) - Method in class weka.core.Instances

Renames the value of a nominal (or string) attribute value.

renameNodeValue(int, String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

change the name of a value of a node

RenameNominalValues - Class in weka.filters.unsupervised.attribute

Renames the values of nominal attributes.

RenameNominalValues() - Constructor for class weka.filters.unsupervised.attribute.RenameNominalValues

rendererName() - Method in interface weka.gui.beans.OffscreenChartRenderer

The name of this off screen renderer

rendererName() - Method in class weka.gui.beans.WekaOffscreenChartRenderer

The name of this off screen renderer

renderHistogram(int, int, List<Instances>, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer

Render histogram(s) (numeric attribute) or bar chart(s) (nominal attribute).

renderHistogram(int, int, List<Instances>, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer

Render histogram(s) (numeric attribute) or pie chart (nominal attribute).

renderXYLineChart(int, int, List<Instances>, String, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer

Render an XY line chart

renderXYLineChart(int, int, List<Instances>, String, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer

Render an XY line chart

renderXYScatterPlot(int, int, List<Instances>, String, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer

Render an XY scatter plot

renderXYScatterPlot(int, int, List<Instances>, String, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer

Render an XY scatter plot

Reorder - Class in weka.filters.unsupervised.attribute

A filter that generates output with a new order of the attributes.

Reorder() - Constructor for class weka.filters.unsupervised.attribute.Reorder

RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.global

This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.

RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.local

This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.

RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

replaceAllBy(Stack<T>) - Method in class weka.core.neighboursearch.covertrees.Stack

Replace all elements in the stack with the elements of another given stack.

replaceAllTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the tip text for this property.

replaceAttributeAt(Attribute, int) - Method in class weka.core.Instances

Replaces the attribute at the given position (0 to numAttributes()) with the given attribute and sets all its values to be missing.

replaceMissingValues(double[]) - Method in class weka.core.BinarySparseInstance

Does nothing, since we don't support missing values.

replaceMissingValues(double[]) - Method in class weka.core.DenseInstance

Replaces all missing values in the instance with the values contained in the given array.

replaceMissingValues(double[]) - Method in interface weka.core.Instance

Replaces all missing values in the instance with the values contained in the given array.

replaceMissingValues(double[]) - Method in class weka.core.SparseInstance

Replaces all missing values in the instance with the values contained in the given array.

ReplaceMissingValues - Class in weka.filters.unsupervised.attribute

Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.

ReplaceMissingValues() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingValues

replaceMissingValuesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the tip text for this property

replaceMissingWithMAX_VALUE(double[]) - Static method in class weka.core.Utils

Replaces all "missing values" in the given array of double values with MAX_VALUE.

ReplaceMissingWithUserConstant - Class in weka.filters.unsupervised.attribute

Replaces all missing values for nominal, string, numeric and date attributes in the dataset with user-supplied constant values.

ReplaceMissingWithUserConstant() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

replaceSubstring(String, String, String) - Static method in class weka.core.Utils

Replaces with a new string, all occurrences of a string from another string.

replaceTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Returns the tip text for this property.

replot() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Quickly replot the display using cached probability estimates

RepositoryIndexGenerator - Class in weka.core

Class for generating html index files and supporting text files for a Weka package meta data repository.

RepositoryIndexGenerator() - Constructor for class weka.core.RepositoryIndexGenerator

repoZipArchiveSize() - Static method in class weka.core.WekaPackageManager

Retrieves the size (in KB) of the repository zip archive stored on the server.

representCopiesUsingWeightsTipText() - Method in class weka.classifiers.meta.Bagging

Returns the tip text for this property

REPTree - Class in weka.classifiers.trees

Fast decision tree learner.

REPTree() - Constructor for class weka.classifiers.trees.REPTree

resample(Random) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement.

Resample - Class in weka.filters.supervised.instance

Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory.

Resample() - Constructor for class weka.filters.supervised.instance.Resample

Resample - Class in weka.filters.unsupervised.instance

Produces a random subsample of a dataset using either sampling with replacement or without replacement.

Resample() - Constructor for class weka.filters.unsupervised.instance.Resample

resampleWithWeights(Random) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.

resampleWithWeights(Random, boolean[]) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.

resampleWithWeights(Random, boolean) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.

resampleWithWeights(Random, boolean[], boolean) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.

resampleWithWeights(Random, double[]) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.

resampleWithWeights(Random, double[], boolean[]) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.

resampleWithWeights(Random, double[], boolean[], boolean) - Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.

ReservoirSample - Class in weka.filters.unsupervised.instance

Produces a random subsample of a dataset using the reservoir sampling Algorithm "R" by Vitter.

ReservoirSample() - Constructor for class weka.filters.unsupervised.instance.ReservoirSample

reset() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Reset the classifier.

reset() - Method in class weka.classifiers.functions.neural.NeuralConnection

Call this to reset the unit for another run.

reset() - Method in class weka.classifiers.functions.neural.NeuralNode

Call this to reset the value and error for this unit, ready for the next run.

reset() - Method in class weka.classifiers.functions.SGD

Reset the classifier.

reset() - Method in class weka.classifiers.functions.SGDText

Reset the classifier.

reset() - Method in class weka.core.converters.AbstractFileLoader

Resets the loader ready to read a new data set

reset() - Method in class weka.core.converters.AbstractLoader

Default implementation sets retrieval mode to NONE

reset() - Method in class weka.core.converters.ArffLoader

Resets the Loader ready to read a new data set or the same data set again.

reset() - Method in class weka.core.converters.C45Loader

Resets the Loader ready to read a new data set or the same data set again.

reset() - Method in class weka.core.converters.ConverterUtils.DataSource

resets the loader.

reset() - Method in class weka.core.converters.CSVLoader

reset() - Method in class weka.core.converters.DatabaseLoader

Resets the Loader ready to read a new data set using set options

reset() - Method in class weka.core.converters.JSONLoader

Resets the Loader ready to read a new data set.

reset() - Method in class weka.core.converters.LibSVMLoader

Resets the Loader ready to read a new data set.

reset() - Method in interface weka.core.converters.Loader

Resets the Loader object ready to begin loading.

reset() - Method in class weka.core.converters.MatlabLoader

Resets the Loader ready to read a new data set.

reset() - Method in class weka.core.converters.SerializedInstancesLoader

Resets the Loader ready to read a new data set

reset() - Method in class weka.core.converters.SVMLightLoader

Resets the Loader ready to read a new data set.

reset() - Method in class weka.core.converters.TextDirectoryLoader

Resets the loader ready to read a new data set

reset() - Method in class weka.core.converters.XRFFLoader

Resets the Loader ready to read a new data set

reset() - Method in class weka.core.neighboursearch.PerformanceStats

Resets all internal fields/counters.

reset() - Method in class weka.core.neighboursearch.TreePerformanceStats

Resets all internal fields/counters.

resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split

Sets distribution associated with model.

resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.C45Split

Sets distribution associated with model.

resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Sets distribution associated with model.

resetFileFilters() - Method in class weka.gui.beans.FileEnvironmentField

Resets the list of choosable file filters.

resetOptions() - Method in class weka.associations.Apriori

Resets the options to the default values.

resetOptions() - Method in class weka.associations.FPGrowth

Reset all options to their default values.

resetOptions() - Method in class weka.core.converters.AbstractFileSaver

resets the options

resetOptions() - Method in class weka.core.converters.AbstractSaver

resets the options

resetOptions() - Method in class weka.core.converters.ArffSaver

Resets the Saver

resetOptions() - Method in class weka.core.converters.C45Saver

Resets the Saver

resetOptions() - Method in class weka.core.converters.CSVSaver

Resets the Saver.

resetOptions() - Method in class weka.core.converters.DatabaseLoader

Resets the Loader to the settings in either the default DatabaseUtils.props or any property file that the user has specified via setCustomPropsFile().

resetOptions() - Method in class weka.core.converters.DatabaseSaver

Resets the Saver ready to save a new data set.

resetOptions() - Method in class weka.core.converters.JSONSaver

Resets the Saver.

resetOptions() - Method in class weka.core.converters.LibSVMSaver

Resets the Saver

resetOptions() - Method in class weka.core.converters.MatlabSaver

Resets the Saver.

resetOptions() - Method in class weka.core.converters.SerializedInstancesSaver

Resets the Saver.

resetOptions() - Method in class weka.core.converters.SVMLightSaver

Resets the Saver.

resetOptions() - Method in class weka.core.converters.XRFFSaver

Resets the Saver

resetStructure() - Method in class weka.core.converters.AbstractSaver

Resets the structure (header information of the instances)

resetStructure() - Method in class weka.core.converters.DatabaseLoader

Resets the structure of instances

resetTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

resetWriter() - Method in class weka.core.converters.AbstractFileSaver

Sets the writer to null.

resetWriter() - Method in class weka.core.converters.SerializedInstancesSaver

Resets the writer, setting writer and objectstream to null.

ResidualModelSelection - Class in weka.classifiers.trees.lmt

Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals.

ResidualModelSelection(int) - Constructor for class weka.classifiers.trees.lmt.ResidualModelSelection

Constructor to create ResidualModelSelection object.

ResidualSplit - Class in weka.classifiers.trees.lmt

Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.

ResidualSplit(int) - Constructor for class weka.classifiers.trees.lmt.ResidualSplit

Creates a split object

restoreBeans(int, int) - Method in class weka.gui.beans.MetaBean

restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection

Call this to have the connection restore from the saved weights.

restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralNode

Call this to have the connection restore from the saved weights.

restoreWindows() - Method in class weka.gui.Main

restores all windows.

resultChanged(ResultChangedEvent) - Method in interface weka.gui.sql.event.ResultChangedListener

This method gets called when a query has been executed.

resultChanged(ResultChangedEvent) - Method in class weka.gui.sql.SqlViewer

This method gets called when a query has been executed.

resultChanged(ResultChangedEvent) - Method in class weka.gui.sql.SqlViewerDialog

This method gets called when a query has been executed.

ResultChangedEvent - Class in weka.gui.sql.event

An event that is generated when a different Result is activated in the ResultPanel.

ResultChangedEvent(Object, String, String, String, String) - Constructor for class weka.gui.sql.event.ResultChangedEvent

constructs the event

ResultChangedListener - Interface in weka.gui.sql.event

A listener that is notified if another Result is activated in the ResultPanel.

RESULTFEATURE - Enum in weka.core.pmml.jaxbbindings

Java class for RESULT-FEATURE.

ResultField - Class in weka.core.pmml.jaxbbindings

Java class for ResultField element declaration.

ResultField() - Constructor for class weka.core.pmml.jaxbbindings.ResultField

ResultHistoryPanel - Class in weka.gui

A component that accepts named stringbuffers and displays the name in a list box.

ResultHistoryPanel(JTextComponent) - Constructor for class weka.gui.ResultHistoryPanel

Create the result history object

ResultHistoryPanel.RKeyAdapter - Class in weka.gui

Extension of KeyAdapter that implements Serializable.

ResultHistoryPanel.RKeyAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RKeyAdapter

ResultHistoryPanel.RMouseAdapter - Class in weka.gui

Extension of MouseAdapter that implements Serializable.

ResultHistoryPanel.RMouseAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RMouseAdapter

ResultListener - Interface in weka.experiment

Interface for objects able to listen for results obtained by a ResultProducer

ResultMatrix - Class in weka.experiment

This matrix is a container for the datasets and classifier setups and their statistics.

ResultMatrix() - Constructor for class weka.experiment.ResultMatrix

initializes the matrix as 1x1 matrix.

ResultMatrix(int, int) - Constructor for class weka.experiment.ResultMatrix

initializes the matrix with the given dimensions.

ResultMatrix(ResultMatrix) - Constructor for class weka.experiment.ResultMatrix

initializes the matrix with the values from the given matrix.

ResultMatrixCSV - Class in weka.experiment

Generates the matrix in CSV ('comma-separated values') format.

ResultMatrixCSV() - Constructor for class weka.experiment.ResultMatrixCSV

initializes the matrix as 1x1 matrix.

ResultMatrixCSV(int, int) - Constructor for class weka.experiment.ResultMatrixCSV

initializes the matrix with the given dimensions.

ResultMatrixCSV(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixCSV

initializes the matrix with the values from the given matrix.

ResultMatrixGnuPlot - Class in weka.experiment

Generates output for a data and script file for GnuPlot.

ResultMatrixGnuPlot() - Constructor for class weka.experiment.ResultMatrixGnuPlot

initializes the matrix as 1x1 matrix.

ResultMatrixGnuPlot(int, int) - Constructor for class weka.experiment.ResultMatrixGnuPlot

initializes the matrix with the given dimensions.

ResultMatrixGnuPlot(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixGnuPlot

initializes the matrix with the values from the given matrix.

ResultMatrixHTML - Class in weka.experiment

Generates the matrix output as HTML.

ResultMatrixHTML() - Constructor for class weka.experiment.ResultMatrixHTML

initializes the matrix as 1x1 matrix.

ResultMatrixHTML(int, int) - Constructor for class weka.experiment.ResultMatrixHTML

initializes the matrix with the given dimensions.

ResultMatrixHTML(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixHTML

initializes the matrix with the values from the given matrix.

ResultMatrixLatex - Class in weka.experiment

Generates the matrix output in LaTeX-syntax.

ResultMatrixLatex() - Constructor for class weka.experiment.ResultMatrixLatex

initializes the matrix as 1x1 matrix.

ResultMatrixLatex(int, int) - Constructor for class weka.experiment.ResultMatrixLatex

initializes the matrix with the given dimensions.

ResultMatrixLatex(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixLatex

initializes the matrix with the values from the given matrix.

ResultMatrixPlainText - Class in weka.experiment

Generates the output as plain text (for fixed width fonts).

ResultMatrixPlainText() - Constructor for class weka.experiment.ResultMatrixPlainText

initializes the matrix as 1x1 matrix.

ResultMatrixPlainText(int, int) - Constructor for class weka.experiment.ResultMatrixPlainText

initializes the matrix with the given dimensions.

ResultMatrixPlainText(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixPlainText

initializes the matrix with the values from the given matrix.

ResultMatrixSignificance - Class in weka.experiment

Only outputs the significance indicators.

ResultMatrixSignificance() - Constructor for class weka.experiment.ResultMatrixSignificance

initializes the matrix as 1x1 matrix.

ResultMatrixSignificance(int, int) - Constructor for class weka.experiment.ResultMatrixSignificance

initializes the matrix with the given dimensions.

ResultMatrixSignificance(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixSignificance

initializes the matrix with the values from the given matrix.

ResultPanel - Class in weka.gui.sql

Represents a panel for displaying the results of a query in table format.

ResultPanel(JFrame) - Constructor for class weka.gui.sql.ResultPanel

initializes the panel

ResultProducer - Interface in weka.experiment

This interface defines the methods required for an object that produces results for different randomizations of a dataset.

resultProducerTipText() - Method in class weka.experiment.AveragingResultProducer

Returns the tip text for this property

resultProducerTipText() - Method in class weka.experiment.DatabaseResultProducer

Returns the tip text for this property

resultProducerTipText() - Method in class weka.experiment.LearningRateResultProducer

Returns the tip text for this property

ResultSetHelper - Class in weka.gui.sql

Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.

ResultSetHelper(ResultSet) - Constructor for class weka.gui.sql.ResultSetHelper

initializes the helper, with unlimited number of rows.

ResultSetHelper(ResultSet, int) - Constructor for class weka.gui.sql.ResultSetHelper

initializes the helper, with the given maximum number of rows (less than 1 means unlimited).

resultsetKey() - Method in class weka.experiment.PairedTTester

Creates a key that maps resultset numbers to their descriptions.

resultsetKey() - Method in interface weka.experiment.Tester

Creates a key that maps resultset numbers to their descriptions.

ResultSetTable - Class in weka.gui.sql

Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.

ResultSetTable(String, String, String, String, ResultSetTableModel) - Constructor for class weka.gui.sql.ResultSetTable

initializes the table

ResultSetTableCellRenderer - Class in weka.gui.sql

Handles the background colors for missing values differently than the DefaultTableCellRenderer.

ResultSetTableCellRenderer() - Constructor for class weka.gui.sql.ResultSetTableCellRenderer

initializes the Renderer with a standard color

ResultSetTableCellRenderer(Color, Color) - Constructor for class weka.gui.sql.ResultSetTableCellRenderer

initializes the Renderer with the given colors

ResultSetTableModel - Class in weka.gui.sql

The model for an SQL ResultSet.

ResultSetTableModel(ResultSet) - Constructor for class weka.gui.sql.ResultSetTableModel

initializes the model, retrieves all rows.

ResultSetTableModel(ResultSet, int) - Constructor for class weka.gui.sql.ResultSetTableModel

initializes the model, retrieves only the given amount of rows (0 means all).

ResultsPanel - Class in weka.gui.experiment

This panel controls simple analysis of experimental results.

ResultsPanel() - Constructor for class weka.gui.experiment.ResultsPanel

Creates the results panel with no initial experiment.

retainAll(Collection<?>) - Method in class weka.core.Trie

Retains only the elements in this collection that are contained in the specified collection

retrieveDir() - Method in class weka.core.converters.AbstractFileSaver

Gets the directory

retrieveDir() - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

retrieveDir() - Method in interface weka.core.converters.Saver

Gets the driectory of the output file This method is used in the KnowledgeFlow GUI.

retrieveFile() - Method in class weka.core.converters.AbstractFileLoader

get the File specified as the source

retrieveFile() - Method in class weka.core.converters.AbstractFileSaver

Gets the destination file.

retrieveFile() - Method in class weka.core.converters.ArffLoader

get the File specified as the source

retrieveFile() - Method in interface weka.core.converters.FileSourcedConverter

Return the current source file/ destination file

retrieveHeadlessEvents() - Method in class weka.gui.beans.CostBenefitAnalysis

Get the list of events processed in headless mode.

retrieveHeadlessEvents() - Method in class weka.gui.beans.DataVisualizer

Get the list of events processed in headless mode.

retrieveHeadlessEvents() - Method in interface weka.gui.beans.HeadlessEventCollector

Get the list of events processed in headless mode.

retrieveHeadlessEvents() - Method in class weka.gui.beans.ModelPerformanceChart

Get the list of events processed in headless mode.

retrieveHeadlessEvents() - Method in class weka.gui.beans.TextViewer

Get the list of events processed in headless mode.

retrieveInstances() - Method in class weka.experiment.InstanceQuery

Makes a database query using the query set through the -Q option to convert a table into a set of instances

retrieveInstances(InstanceQueryAdapter, ResultSet) - Static method in class weka.experiment.InstanceQuery

retrieveInstances(String) - Method in class weka.experiment.InstanceQuery

Makes a database query to convert a table into a set of instances

retrieveURL() - Method in class weka.core.converters.ArffLoader

Return the current url

retrieveURL() - Method in class weka.core.converters.JSONLoader

Return the current url.

retrieveURL() - Method in class weka.core.converters.LibSVMLoader

Return the current url.

retrieveURL() - Method in class weka.core.converters.MatlabLoader

Return the current url.

retrieveURL() - Method in class weka.core.converters.SVMLightLoader

Return the current url.

retrieveURL() - Method in interface weka.core.converters.URLSourcedLoader

Return the current url

retrieveURL() - Method in class weka.core.converters.XRFFLoader

Return the current url

returnLeaves(ArrayList<RuleNode>[]) - Method in class weka.classifiers.trees.m5.RuleNode

Return a list containing all the leaves in the tree

rev() - Method in class weka.core.matrix.DoubleVector

Returns the reverse vector

REVERSED - Static variable in interface weka.gui.graphvisualizer.GraphConstants

Types of Edges

reversedArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader

Count nr of reversed arcs from other network compared to current network

revertNewLines(String) - Static method in class weka.core.Utils

Reverts \r and \n in a string into carriage returns and new lines.

REVISION - Static variable in class weka.core.Version

the revision

RevisionHandler - Interface in weka.core

For classes that should return their source control revision.

RevisionUtils - Class in weka.core

Contains utility functions for handling revisions.

RevisionUtils() - Constructor for class weka.core.RevisionUtils

RevisionUtils.Type - Enum in weka.core

Enumeration of source control types.

ridgeTipText() - Method in class weka.classifiers.functions.LinearRegression

Returns the tip text for this property

ridgeTipText() - Method in class weka.classifiers.functions.Logistic

Returns the tip text for this property

RIGHT_PARENTHESES - Variable in class weka.experiment.ResultMatrix

the right parentheses for enumerating cols/rows.

rightNode() - Method in class weka.classifiers.trees.m5.RuleNode

Get the right child of this node

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split

Prints the condition satisfied by instances in a subset.

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split

Prints the condition satisfied by instances in a subset.

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Prints left side of condition satisfied by instances in subset index.

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Does nothing because no condition has to be satisfied.

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit

Prints the condition satisfied by instances in a subset.

rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit

Does nothing because no condition has to be satisfied.

rightSide(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit

Prints the condition satisfied by instances in a subset.

RINT - Static variable in interface weka.core.mathematicalexpression.sym

RINT - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

rmCoveredBySuccessives(Instances, ArrayList<Rule>, int) - Static method in class weka.classifiers.rules.RuleStats

Static utility function to count the data covered by the rules after the given index in the given rules, and then remove them.

rnorm(int, double, double, Random) - Static method in class weka.core.matrix.Maths

Generates a sample of a normal distribution.

ROC - Class in weka.core.pmml.jaxbbindings

Java class for ROC element declaration.

ROC() - Constructor for class weka.core.pmml.jaxbbindings.ROC

ROCGraph - Class in weka.core.pmml.jaxbbindings

Java class for ROCGraph element declaration.

ROCGraph() - Constructor for class weka.core.pmml.jaxbbindings.ROCGraph

ROOT_FINDER_ACCURACY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

ROOT_FINDER_MAX_ITER - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

How close the root finder for numeric and nominal have to get

ROOT_NODE - Static variable in class weka.core.xml.XMLOptions

the root node.

ROOT_NODE - Static variable in class weka.core.xml.XMLSerialization

the root node of the XML document

rootMeanPriorSquaredError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the root mean prior squared error.

rootMeanPriorSquaredError() - Method in class weka.classifiers.Evaluation

Returns the root mean prior squared error.

rootMeanSquaredError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the root mean squared error.

rootMeanSquaredError() - Method in class weka.classifiers.Evaluation

Returns the root mean squared error.

rootRelativeSquaredError() - Method in class weka.classifiers.evaluation.Evaluation

Returns the root relative squared error if the class is numeric.

rootRelativeSquaredError() - Method in class weka.classifiers.Evaluation

Returns the root relative squared error if the class is numeric.

rotate(double, double, double) - Method in class weka.gui.visualize.PostscriptGraphics

rotate(double) - Method in class weka.gui.visualize.PostscriptGraphics

round(double) - Static method in class weka.core.Utils

Rounds a double to the next nearest integer value.

roundDouble(double, int) - Static method in class weka.core.Utils

Rounds a double to the given number of decimal places.

Row - Class in weka.core.pmml.jaxbbindings

Java class for row element declaration.

Row() - Constructor for class weka.core.pmml.jaxbbindings.Row

rowNameWidthTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

RPAREN - Static variable in interface weka.core.mathematicalexpression.sym

RPAREN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

RSQUARE - Static variable in interface weka.core.json.sym

Rule - Class in weka.classifiers.rules

Abstract class of generic rule

Rule() - Constructor for class weka.classifiers.rules.Rule

Rule - Class in weka.classifiers.trees.m5

Generates a single m5 tree or rule

Rule() - Constructor for class weka.classifiers.trees.m5.Rule

Constructor declaration

RULEFEATURE - Enum in weka.core.pmml.jaxbbindings

Java class for RULE-FEATURE.

RuleNode - Class in weka.classifiers.trees.m5

Constructs a node for use in an m5 tree or rule

RuleNode(double, double, RuleNode) - Constructor for class weka.classifiers.trees.m5.RuleNode

Creates a new RuleNode instance.

RuleSelectionMethod - Class in weka.core.pmml.jaxbbindings

Java class for RuleSelectionMethod element declaration.

RuleSelectionMethod() - Constructor for class weka.core.pmml.jaxbbindings.RuleSelectionMethod

RuleSet - Class in weka.core.pmml.jaxbbindings

Java class for RuleSet element declaration.

RuleSet() - Constructor for class weka.core.pmml.jaxbbindings.RuleSet

RuleSetModel - Class in weka.classifiers.pmml.consumer

Class implementing import of PMML RuleSetModel.

RuleSetModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.RuleSetModel

Constructor for a RuleSetModel

RuleSetModel - Class in weka.core.pmml.jaxbbindings

Java class for RuleSetModel element declaration.

RuleSetModel() - Constructor for class weka.core.pmml.jaxbbindings.RuleSetModel

rulesMustContainTipText() - Method in class weka.associations.FPGrowth

Returns the tip text for this property

RuleStats - Class in weka.classifiers.rules

This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.

RuleStats() - Constructor for class weka.classifiers.rules.RuleStats

Default constructor

RuleStats(Instances, ArrayList<Rule>) - Constructor for class weka.classifiers.rules.RuleStats

Constructor that provides ruleset and data

run(Object, String[]) - Method in interface weka.core.CommandlineRunnable

Execute the supplied object.

run() - Method in class weka.gui.beans.FlowRunner

Launch all loaded KnowledgeFlow

run() - Method in class weka.gui.ReaderToTextPane

Sit here listening for lines of input and appending them straight to the text component.

run(File, String[]) - Method in class weka.gui.scripting.Script

Executes the script without loading it first.

run() - Method in class weka.gui.scripting.Script.ScriptThread

Executes the script.

Run - Class in weka

Helper class that executes Weka schemes from the command line.

Run() - Constructor for class weka.Run

Run.SchemeType - Enum in weka

RUN_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer

The name of the key field containing the run number

RUN_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer

The name of the key field containing the run number.

RUN_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer

The name of the key field containing the run number

runAssociator(Associator, String[]) - Static method in class weka.associations.AbstractAssociator

runs the associator with the given commandline options

runClassifier(Classifier, String[]) - Static method in class weka.classifiers.AbstractClassifier

runs the classifier instance with the given options.

runClusterer(Clusterer, String[]) - Static method in class weka.clusterers.AbstractClusterer

runs the clusterer instance with the given options.

runCommand(String) - Method in class weka.gui.SimpleCLIPanel

Executes a simple cli command.

runDataGenerator(DataGenerator, String[]) - Static method in class weka.datagenerators.DataGenerator

runs the datagenerator instance with the given options.

runEvaluator(ASEvaluation, String[]) - Static method in class weka.attributeSelection.ASEvaluation

runs the evaluator with the given commandline options

runExperiment(boolean) - Method in class weka.experiment.Experiment

runExperiment() - Method in class weka.experiment.Experiment

Runs all iterations of the experiment, continuing past errors.

runExperiment() - Method in class weka.experiment.RemoteExperiment

Overides runExperiment in Experiment

runFileLoader(AbstractFileLoader, String[]) - Static method in class weka.core.converters.AbstractFileLoader

runs the given loader with the provided options

runFileSaver(AbstractFileSaver, String[]) - Static method in class weka.core.converters.AbstractFileSaver

runs the given saver with the specified options

runFilter(Filter, String[]) - Static method in class weka.filters.Filter

runs the filter instance with the given options.

RunNumberPanel - Class in weka.gui.experiment

This panel controls configuration of lower and upper run numbers in an experiment.

RunNumberPanel() - Constructor for class weka.gui.experiment.RunNumberPanel

Creates the panel with no initial experiment.

RunNumberPanel(Experiment) - Constructor for class weka.gui.experiment.RunNumberPanel

Creates the panel with the supplied initial experiment.

RunPanel - Class in weka.gui.experiment

This panel controls the running of an experiment.

RunPanel() - Constructor for class weka.gui.experiment.RunPanel

Creates the run panel with no initial experiment.

RunPanel(Experiment) - Constructor for class weka.gui.experiment.RunPanel

Creates the panel with the supplied initial experiment.

runScript(Script, String[]) - Static method in class weka.gui.scripting.Script

Runs the specified script.

runsTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

runsTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

runsTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

runsTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

runsTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

runsTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

runsTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

runsTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

runTokenizer(Tokenizer, String[]) - Static method in class weka.core.tokenizers.Tokenizer

initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.

S

s_atLeastOnePackageUpgradeHasOccurredInThisSession - Static variable in class weka.gui.PackageManager

s_fileFormatsAvailable - Static variable in class weka.gui.beans.SerializedModelSaver

Available file formats.

s_numericAfterDecimalPoint - Static variable in class weka.core.AbstractInstance

Default max number of digits after the decimal point for numeric values

s_startupListeners - Static variable in class weka.gui.beans.KnowledgeFlowApp

SAMPLE_SIZE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

attribute name: Sample Size

sampleSizePercentTipText() - Method in class weka.filters.supervised.instance.Resample

Returns the tip text for this property.

sampleSizePercentTipText() - Method in class weka.filters.unsupervised.instance.Resample

Returns the tip text for this property

sampleSizeTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the tip text for this property

sampleSizeTipText() - Method in class weka.filters.unsupervised.instance.ReservoirSample

Returns the tip text for this property

save(StringBuffer) - Method in class weka.gui.SaveBuffer

Save a buffer

save() - Method in class weka.gui.scripting.Script

Saves the file under with the current filename.

save(File, String) - Static method in class weka.gui.scripting.ScriptUtils

Saves the content to a file.

saveAs(File) - Method in class weka.gui.scripting.Script

Saves the file under with the given filename (and updates the internal filename).

saveBatch() - Method in class weka.gui.beans.Saver

Saves instances in batch mode

saveBinary(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver

Save a model in binary form.

SaveBuffer - Class in weka.gui

This class handles the saving of StringBuffers to files.

SaveBuffer(Logger, Component) - Constructor for class weka.gui.SaveBuffer

Constructor

saveComponent() - Method in class weka.gui.visualize.PrintableComponent

displays a save dialog for saving the panel to a file.

saveComponent() - Method in interface weka.gui.visualize.PrintableHandler

displays a save dialog for saving the component to a file.

saveComponent() - Method in class weka.gui.visualize.PrintablePanel

displays a save dialog for saving the panel to a file.

saveFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

saves the current data into a file

saveFileAs() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

saves the current data into a new file

saveInstanceDataTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

saveInstanceDataTipText() - Method in class weka.clusterers.Cobweb

Returns the tip text for this property

saveInstancesTipText() - Method in class weka.classifiers.trees.M5P

Returns the tip text for this property

saveInstancesToFile(AbstractFileSaver, Instances) - Method in class weka.gui.explorer.PreprocessPanel

saves the data with the specified saver

saveKOML(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver

Save a model in KOML deep object serialized XML form.

saveLayout(File, int) - Method in class weka.gui.beans.KnowledgeFlowApp

saveLayout(OutputStream, int) - Method in class weka.gui.beans.KnowledgeFlowApp

Save the knowledge flow into the OutputStream passed at input.

saveModel() - Method in class weka.gui.beans.Classifier

saveModel() - Method in class weka.gui.beans.Clusterer

Saver - Interface in weka.core.converters

Interface to something that can save Instances to an output destination in some format.

Saver - Class in weka.gui.beans

Saves data sets using weka.core.converter classes

Saver() - Constructor for class weka.gui.beans.Saver

Contsructor

SAVER_DIALOG - Static variable in class weka.gui.ConverterFileChooser

the saver dialog.

SaverBeanInfo - Class in weka.gui.beans

Bean info class for the saver bean

SaverBeanInfo() - Constructor for class weka.gui.beans.SaverBeanInfo

SaverCustomizer - Class in weka.gui.beans

GUI Customizer for the saver bean

SaverCustomizer() - Constructor for class weka.gui.beans.SaverCustomizer

Constructor

saveSize() - Method in class weka.gui.sql.SqlViewer

obtains the size of the panel and saves it in the history.

saveToFile(String, Object) - Static method in class weka.core.Debug

writes the serialized object to the speicified file

saveWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection

Call this to have the connection save the current weights.

saveWeights() - Method in class weka.classifiers.functions.neural.NeuralNode

Call this to have the connection save the current weights.

saveWorkingInstancesToFileQ() - Method in class weka.gui.explorer.PreprocessPanel

Queries the user for a file to save instances as, then saves the instances in a background process.

saveXStream(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver

Save a model in XStream deep object serialized XML form.

scalarMultiply(double) - Method in class weka.core.AlgVector

Computes the scalar product of this vector with a scalar

scale(int) - Method in class weka.gui.beans.BeanVisual

Reduce this BeanVisual's icon size by the given factor

scale(double) - Method in class weka.gui.beans.BeanVisual

scale(double, double) - Method in class weka.gui.visualize.PostscriptGraphics

scaleTipText() - Method in class weka.filters.unsupervised.attribute.Normalize

Returns the tip text for this property.

Scanner - Class in weka.core.json

A scanner for JSON data files.

Scanner(InputStream, SymbolFactory) - Constructor for class weka.core.json.Scanner

Scanner(Reader, SymbolFactory) - Constructor for class weka.core.json.Scanner

Scanner(Reader) - Constructor for class weka.core.json.Scanner

Creates a new scanner There is also a java.io.InputStream version of this constructor.

Scanner(InputStream) - Constructor for class weka.core.json.Scanner

Creates a new scanner.

Scanner - Class in weka.core.mathematicalexpression

A scanner for mathematical expressions.

Scanner(InputStream, SymbolFactory) - Constructor for class weka.core.mathematicalexpression.Scanner

Scanner(Reader) - Constructor for class weka.core.mathematicalexpression.Scanner

Creates a new scanner There is also a java.io.InputStream version of this constructor.

Scanner(InputStream) - Constructor for class weka.core.mathematicalexpression.Scanner

Creates a new scanner.

Scanner - Class in weka.filters.unsupervised.instance.subsetbyexpression

A scanner for evaluating whether an Instance is to be included in a subset or not.

Scanner(InputStream, SymbolFactory) - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Scanner

Scanner(Reader) - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Scanner

Creates a new scanner There is also a java.io.InputStream version of this constructor.

Scanner(InputStream) - Constructor for class weka.filters.unsupervised.instance.subsetbyexpression.Scanner

Creates a new scanner.

scatter(double[][], double[], double, int) - Static method in class weka.estimators.MultivariateGaussianEstimator

Calculates the scatter matrix of a sample matrix.

ScatterPlotMatrix - Class in weka.gui.beans

Bean that encapsulates weka.gui.visualize.MatrixPanel for displaying a scatter plot matrix.

ScatterPlotMatrix() - Constructor for class weka.gui.beans.ScatterPlotMatrix

ScatterPlotMatrixBeanInfo - Class in weka.gui.beans

Bean info class for the scatter plot matrix bean

ScatterPlotMatrixBeanInfo() - Constructor for class weka.gui.beans.ScatterPlotMatrixBeanInfo

Scoreable - Interface in weka.classifiers.bayes.net.search.local

Interface for allowing to score a classifier

Scorecard - Class in weka.core.pmml.jaxbbindings

Java class for Scorecard element declaration.

Scorecard() - Constructor for class weka.core.pmml.jaxbbindings.Scorecard

ScoreDistribution - Class in weka.core.pmml.jaxbbindings

Java class for ScoreDistribution element declaration.

ScoreDistribution() - Constructor for class weka.core.pmml.jaxbbindings.ScoreDistribution

scoreTypeTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Script - Class in weka.gui.scripting

A simple helper class for loading, saving scripts.

Script() - Constructor for class weka.gui.scripting.Script

Initializes the script.

Script(Document) - Constructor for class weka.gui.scripting.Script

Initializes the script.

Script(Document, File) - Constructor for class weka.gui.scripting.Script

Initializes the script.

Script.ScriptThread - Class in weka.gui.scripting

The Thread for running a script.

Script.ScriptThread(Script, String[]) - Constructor for class weka.gui.scripting.Script.ScriptThread

Initializes the thread.

ScriptExecutionEvent - Class in weka.gui.scripting.event

Event that gets sent when a script is executed.

ScriptExecutionEvent(Script, ScriptExecutionEvent.Type) - Constructor for class weka.gui.scripting.event.ScriptExecutionEvent

Initializes the event.

ScriptExecutionEvent(Script, ScriptExecutionEvent.Type, Object) - Constructor for class weka.gui.scripting.event.ScriptExecutionEvent

Initializes the event.

ScriptExecutionEvent.Type - Enum in weka.gui.scripting.event

Defines the type of event.

ScriptExecutionListener - Interface in weka.gui.scripting.event

For classes that want to be notified about changes in the script execution.

scriptFinished(ScriptExecutionEvent) - Method in interface weka.gui.scripting.event.ScriptExecutionListener

Gets sent when a script execution changes.

scriptFinished(ScriptExecutionEvent) - Method in class weka.gui.scripting.FileScriptingPanel

Gets sent when a script finishes execution.

ScriptingPanel - Class in weka.gui.scripting

Abstract ancestor for scripting panels.

ScriptingPanel() - Constructor for class weka.gui.scripting.ScriptingPanel

Default constructor.

ScriptUtils - Class in weka.gui.scripting

A helper class for Script related stuff.

ScriptUtils() - Constructor for class weka.gui.scripting.ScriptUtils

scrollToVisible(int, int) - Method in class weka.gui.JTableHelper

Assumes table is contained in a JScrollPane.

scrollToVisible(JTable, int, int) - Static method in class weka.gui.JTableHelper

Assumes table is contained in a JScrollPane.

search(ASEvaluation, Instances) - Method in class weka.attributeSelection.ASSearch

Searches the attribute subset/ranking space.

search(ASEvaluation, Instances) - Method in class weka.attributeSelection.BestFirst

Searches the attribute subset space by best first search

search(ASEvaluation, Instances) - Method in class weka.attributeSelection.GreedyStepwise

Searches the attribute subset space by forward selection.

search(ASEvaluation, Instances) - Method in class weka.attributeSelection.Ranker

Kind of a dummy search algorithm.

search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.K2

search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.

search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.K2

search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.

search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

search() - Method in class weka.gui.arffviewer.ArffPanel

searches for a string in the cells

search() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

searches for a string in the cells

search(Vector<HierarchyPropertyParser.TreeNode>, String) - Method in class weka.gui.HierarchyPropertyParser

Helper function to search for the given target string in a given vector in which the elements' value may hopefully is equal to the target.

SearchAlgorithm - Class in weka.classifiers.bayes.net.search

This is the base class for all search algorithms for learning Bayes networks.

SearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.SearchAlgorithm

c'tor

searchAlgorithmTipText() - Method in class weka.classifiers.bayes.BayesNet

searchBackwardsTipText() - Method in class weka.attributeSelection.GreedyStepwise

Returns the tip text for this property

searchFinish() - Method in class weka.core.neighboursearch.PerformanceStats

Signals end of the nearest neighbour search.

searchFinish() - Method in class weka.core.neighboursearch.TreePerformanceStats

Signals end of the nearest neighbour search.

searchPoints(int, int, boolean) - Method in class weka.gui.visualize.Plot2D

Pops up a window displaying attribute information on any instances at a point+-plotting_point_size (in panel coordinates)

searchStart() - Method in class weka.core.neighboursearch.PerformanceStats

Signals start of the nearest neighbour search.

searchStart() - Method in class weka.core.neighboursearch.TreePerformanceStats

Signals start of the nearest neighbour search.

searchTerminationTipText() - Method in class weka.attributeSelection.BestFirst

Returns the tip text for this property

searchTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns the tip text for this property

searchTipText() - Method in class weka.classifiers.rules.DecisionTable

Returns the tip text for this property

searchTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection

Returns the tip text for this property

SeasonalityExpoSmooth - Class in weka.core.pmml.jaxbbindings

Java class for Seasonality_ExpoSmooth element declaration.

SeasonalityExpoSmooth() - Constructor for class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

secondInstanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner

secondInstanceProduced(InstanceEvent) - Method in interface weka.gui.streams.SerialInstanceListener

secondValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

secondValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues

seedTipText() - Method in class weka.attributeSelection.OneRAttributeEval

Returns a string for this option suitable for display in the gui as a tip text

seedTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the tip text for this property

seedTipText() - Method in class weka.attributeSelection.WrapperSubsetEval

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

seedTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

seedTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

seedTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

seedTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

seedTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

seedTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

seedTipText() - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.functions.VotedPerceptron

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.meta.MultiScheme

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableClassifier

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.rules.JRip

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.rules.PART

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.trees.RandomForest

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

seedTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

seedTipText() - Method in class weka.clusterers.Cobweb

Returns the tip text for this property

seedTipText() - Method in class weka.clusterers.RandomizableClusterer

Returns the tip text for this property

seedTipText() - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Returns the tip text for this property

seedTipText() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Returns the tip text for this property

seedTipText() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Returns the tip text for this property.

seedTipText() - Method in class weka.datagenerators.DataGenerator

Returns the tip text for this property

seedTipText() - Method in class weka.filters.supervised.attribute.ClassOrder

Returns the tip text for this property

seedTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Returns the tip text for this property

seedTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the tip text for this property

seedTipText() - Method in class weka.filters.unsupervised.attribute.RandomSubset

Returns the tip text for this property.

seedTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds

Returns the tip text for this property

seedTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker

Tip text for this property

seedTipText() - Method in class weka.gui.beans.TrainTestSplitMaker

Tip text for this property

Segment - Class in weka.core.pmml.jaxbbindings

Java class for Segment element declaration.

Segment() - Constructor for class weka.core.pmml.jaxbbindings.Segment

Segmentation - Class in weka.core.pmml.jaxbbindings

Java class for Segmentation element declaration.

Segmentation() - Constructor for class weka.core.pmml.jaxbbindings.Segmentation

select(int, int[], int, int, int) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".

select(int, int[], int, int, int) - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".

select(String) - Method in class weka.experiment.DatabaseUtils

Executes a SQL SELECT query that returns a ResultSet.

SelectAttributes(ASEvaluation, String[]) - Static method in class weka.attributeSelection.AttributeSelection

Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.

SelectAttributes(Instances) - Method in class weka.attributeSelection.AttributeSelection

Perform attribute selection on the supplied training instances.

SelectAttributes(ASEvaluation, String[], Instances) - Static method in class weka.attributeSelection.AttributeSelection

Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.

selectAttributesCVSplit(Instances) - Method in class weka.attributeSelection.AttributeSelection

Select attributes for a split of the data.

selectedAttributes() - Method in class weka.attributeSelection.AttributeSelection

get the final selected set of attributes.

selectedAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Returns the tip text for this property

SelectedTag - Class in weka.core

Represents a selected value from a finite set of values, where each value is a Tag (i.e.

SelectedTag(int, Tag[]) - Constructor for class weka.core.SelectedTag

Creates a new SelectedTag instance.

SelectedTag(String, Tag[]) - Constructor for class weka.core.SelectedTag

Creates a new SelectedTag instance.

SelectedTagEditor - Class in weka.gui

A PropertyEditor that uses tags, where the tags are obtained from a weka.core.SelectedTag object.

SelectedTagEditor() - Constructor for class weka.gui.SelectedTagEditor

SELECTION_GREEDY - Static variable in class weka.classifiers.functions.LinearRegression

Attribute selection method: Greedy method

SELECTION_M5 - Static variable in class weka.classifiers.functions.LinearRegression

Attribute selection method: M5 method

SELECTION_NONE - Static variable in class weka.classifiers.functions.LinearRegression

Attribute selection method: No attribute selection

selectModel(Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection

Selects C4.5-type split for the given dataset.

selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection

Selects C4.5-type split for the given dataset.

selectModel(Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection

Selects C4.5-type split for the given dataset.

selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection

Selects C4.5-type split for the given dataset.

selectModel(Instances) - Method in class weka.classifiers.trees.j48.ModelSelection

Selects a model for the given dataset.

selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.ModelSelection

Selects a model for the given train data using the given test data

selectModel(Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection

Selects NBTree-type split for the given dataset.

selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection

Selects NBTree-type split for the given dataset.

selectModel(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection

Selects split based on residuals for the given dataset.

selectModel(Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection

Method not in use

selectModel(Instances, Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection

Method not in use

SEND_INSTANCES - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

Command to remove instances from this node and send them to the VisualizePanel.

seq(int, int) - Static method in class weka.core.matrix.IntVector

Generates an IntVector that stores all integers inclusively between two integers.

Sequence - Class in weka.core.pmml.jaxbbindings

Java class for Sequence element declaration.

Sequence() - Constructor for class weka.core.pmml.jaxbbindings.Sequence

SequenceModel - Class in weka.core.pmml.jaxbbindings

Java class for SequenceModel element declaration.

SequenceModel() - Constructor for class weka.core.pmml.jaxbbindings.SequenceModel

SequenceReference - Class in weka.core.pmml.jaxbbindings

Java class for SequenceReference element declaration.

SequenceReference() - Constructor for class weka.core.pmml.jaxbbindings.SequenceReference

SequenceRule - Class in weka.core.pmml.jaxbbindings

Java class for SequenceRule element declaration.

SequenceRule() - Constructor for class weka.core.pmml.jaxbbindings.SequenceRule

SERIAL_VERSION_UID - Static variable in class weka.core.SerializationHelper

the field name of serialVersionUID.

SerialInstanceListener - Interface in weka.gui.streams

Defines an interface for objects able to produce two output streams of instances.

SerializationHelper - Class in weka.core

A helper class for determining serialVersionUIDs and checking whether classes contain one and/or need one.

SerializationHelper() - Constructor for class weka.core.SerializationHelper

serialize(Object) - Static method in class weka.core.xml.XStream

Serializes the supplied object xml

SERIALIZED_OBJ_FILE_EXTENSION - Static variable in class weka.core.Instances

The filename extension that should be used for bin.

SerializedClassifier - Class in weka.classifiers.misc

A wrapper around a serialized classifier model.

SerializedClassifier() - Constructor for class weka.classifiers.misc.SerializedClassifier

serializedClassifierFileTipText() - Method in class weka.filters.supervised.attribute.AddClassification

Returns the tip text for this property.

serializedClustererFileTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster

Returns the tip text for this property.

SerializedInstancesLoader - Class in weka.core.converters

Reads a source that contains serialized Instances.

SerializedInstancesLoader() - Constructor for class weka.core.converters.SerializedInstancesLoader

SerializedInstancesSaver - Class in weka.core.converters

Serializes the instances to a file with extension bsi.

SerializedInstancesSaver() - Constructor for class weka.core.converters.SerializedInstancesSaver

Constructor.

SerializedModelSaver - Class in weka.gui.beans

A bean that saves serialized models

SerializedModelSaver() - Constructor for class weka.gui.beans.SerializedModelSaver

Constructor.

SerializedModelSaverBeanInfo - Class in weka.gui.beans

Bean info class for the serialized model saver bean

SerializedModelSaverBeanInfo() - Constructor for class weka.gui.beans.SerializedModelSaverBeanInfo

SerializedModelSaverCustomizer - Class in weka.gui.beans

GUI Customizer for the SerializedModelSaver bean

SerializedModelSaverCustomizer() - Constructor for class weka.gui.beans.SerializedModelSaverCustomizer

Constructor

SerializedObject - Class in weka.core

Class for storing an object in serialized form in memory.

SerializedObject(Object) - Constructor for class weka.core.SerializedObject

Creates a new serialized object (without compression).

SerializedObject(Object, boolean) - Constructor for class weka.core.SerializedObject

Creates a new serialized object.

serializePMMLModel(PMMLModel, String) - Static method in class weka.core.pmml.PMMLFactory

Serialize a PMMLModel object that encapsulates a PMML model

serializePMMLModel(PMMLModel, File) - Static method in class weka.core.pmml.PMMLFactory

Serialize a PMMLModel object that encapsulates a PMML model

serializePMMLModel(PMMLModel, OutputStream) - Static method in class weka.core.pmml.PMMLFactory

Serialize a PMMLModel object that encapsulates a PMML model

SerialUIDChanger - Class in weka.core.xml

This class enables one to change the UID of a serialized object and therefore not losing the data stored in the binary format.

SerialUIDChanger() - Constructor for class weka.core.xml.SerialUIDChanger

set(int, Instance) - Method in class weka.core.Instances

Replaces the instance at the given position.

set(int, double) - Method in class weka.core.matrix.DoubleVector

Set a single element.

set(double) - Method in class weka.core.matrix.DoubleVector

Set all elements to a value

set(int, int, double) - Method in class weka.core.matrix.DoubleVector

Set some elements to a value

set(int, int, double[], int) - Method in class weka.core.matrix.DoubleVector

Set some elements using a 2-D array

set(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Set the elements using a DoubleVector

set(int, int, DoubleVector, int) - Method in class weka.core.matrix.DoubleVector

Set some elements using a DoubleVector.

set(int) - Method in class weka.core.matrix.IntVector

Sets the value of an element.

set(int, int, int[], int) - Method in class weka.core.matrix.IntVector

Sets the values of elements from an int array.

set(int, int, IntVector, int) - Method in class weka.core.matrix.IntVector

Sets the values of elements from another IntVector.

set(IntVector) - Method in class weka.core.matrix.IntVector

Sets the values of elements from another IntVector.

set(int, int) - Method in class weka.core.matrix.IntVector

Sets a single element.

set(int, int, double) - Method in class weka.core.matrix.Matrix

Set a single element.

set(int, T) - Method in class weka.core.neighboursearch.covertrees.Stack

Sets the ith element in the stack.

set(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Replaces the element at the specified position in this list with the specified element.

set(String, String) - Static method in class weka.gui.explorer.ExplorerDefaults

setAbsoluteValue(Double) - Method in class weka.core.pmml.jaxbbindings.Coefficients

Sets the value of the absoluteValue property.

setActivationFunction(ACTIVATIONFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the activationFunction property.

setActivationFunction(ACTIVATIONFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the activationFunction property.

setActive(boolean) - Method in class weka.gui.beans.AttributeSummarizer

Set active status of this perspective.

setActive(boolean) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Set active status of this perspective.

setActive(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setActive(boolean) - Method in class weka.gui.beans.ScatterPlotMatrix

Set active status of this perspective.

setActive(boolean) - Method in class weka.gui.beans.SQLViewerPerspective

Set active status of this perspective.

setActiveTab(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setAcuity(double) - Method in class weka.clusterers.Cobweb

set the acuity.

setAdditionalMeasures(String[]) - Method in class weka.experiment.AveragingResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator

Set a list of method names for additional measures to look for in Classifiers.

setAdditionalMeasures(String[]) - Method in class weka.experiment.CrossValidationResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.DatabaseResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Set a list of method names for additional measures to look for in Classifiers.

setAdditionalMeasures(String[]) - Method in class weka.experiment.ExplicitTestsetResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.LearningRateResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.RandomSplitResultProducer

Set a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in class weka.experiment.RegressionSplitEvaluator

Set a list of method names for additional measures to look for in Classifiers.

setAdditionalMeasures(String[]) - Method in interface weka.experiment.ResultProducer

Sets a list of method names for additional measures to look for in SplitEvaluators.

setAdditionalMeasures(String[]) - Method in interface weka.experiment.SplitEvaluator

Sets a list of method names for additional measures to look for in SplitEvaluators.

setAddMatchingEndBlocks(boolean) - Method in class weka.gui.scripting.SyntaxDocument

Sets whether matching block ends are inserted or not.

setAdjRSquared(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the adjRSquared property.

setAdjustWeights(boolean) - Method in class weka.filters.supervised.instance.SpreadSubsample

Sets whether the instance weights will be adjusted to maintain total weight per class.

setAdvanceDataSetFirst(boolean) - Method in class weka.experiment.Experiment

Set the value of m_AdvanceDataSetFirst.

setAffinity(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the affinity property.

setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the aggregate property.

setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the aggregate property.

setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the aggregate property.

setAIC(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the aic property.

setAICc(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the aiCc property.

setAlgorithm(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the algorithm property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.MiningModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Sets the value of the algorithmName property.

setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the algorithmName property.

setAllowMultipleTabs(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp

setAllowUnclassifiedInstances(boolean) - Method in class weka.classifiers.trees.RandomTree

Set the value of AllowUnclassifiedInstances.

setAlpha(double) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Set prior used in probability table estimation

setAlpha(Double) - Method in class weka.core.pmml.jaxbbindings.Level

Sets the value of the alpha property.

setAlternate(Alternate) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the alternate property.

setAlternateTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Sets the value of the alternateTargetCategory property.

setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the altitude property.

setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the altitude property.

setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron

Sets the value of the altitude property.

setAmplitude(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Sets the amplitude multiplier.

setAnimated() - Method in class weka.gui.beans.BeanVisual

Deprecated.

setAnova(Anova) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the anova property.

setAntecedent(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the antecedent property.

setAnyDistribution(AnyDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate

Sets the value of the anyDistribution property.

setAnyDistribution(AnyDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the anyDistribution property.

setAppend(boolean) - Method in class weka.gui.beans.TextSaver

setAppendPredictedProbabilities(boolean) - Method in class weka.gui.beans.PredictionAppender

Set whether to append predicted probabilities rather than class value (for discrete class data sets)

setApplication(Application) - Method in class weka.core.pmml.jaxbbindings.Header

Sets the value of the application property.

setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the apply property.

setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the apply property.

setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the apply property.

setAppropriateSize() - Method in class weka.classifiers.bayes.net.GUI

Sets the preferred size for m_GraphPanel GraphPanel to the minimum size that is neccessary to display the graph.

setArffFile(String) - Method in class weka.gui.streams.InstanceLoader

setArffFile(String) - Method in class weka.gui.streams.InstanceSavePanel

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.BoundaryValues

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.ClassLabels

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.CorrelationFields

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TextDictionary

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TimeException

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.XCoordinates

Sets the value of the array property.

setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.YCoordinates

Sets the value of the array property.

setAssociatedConnections(Vector<BeanConnection>) - Method in class weka.gui.beans.MetaBean

setAssociationModel(AssociationModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the associationModel property.

setAssociator(Associator) - Method in class weka.associations.CheckAssociator

Set the associator to test.

setAssociator(Associator) - Method in class weka.associations.SingleAssociatorEnhancer

Set the base associator.

setAssociator(Associator) - Method in class weka.gui.beans.Associator

Set the associator for this wrapper

setAsText(String) - Method in class weka.gui.beans.EnvironmentField

setAsText(String) - Method in class weka.gui.CostMatrixEditor

Some objects can be represented as text, but a cost matrix cannot.

setAsText(String) - Method in class weka.gui.GenericArrayEditor

Returns null as we don't support getting/setting values as text.

setAsText(String) - Method in class weka.gui.GenericObjectEditor

Returns null as we don't support getting/setting values as text.

setAsText(String) - Method in class weka.gui.SelectedTagEditor

Sets the current property value as text.

setAsText(String) - Method in class weka.gui.SimpleDateFormatEditor

Sets the date format string.

setAttList_Irr(boolean[]) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the array that defines which of the attributes are seen to be irrelevant.

setAttribute(int) - Method in class weka.gui.AttributeSummaryPanel

Sets the attribute that statistics will be displayed for.

setAttribute(int) - Method in class weka.gui.AttributeVisualizationPanel

Tells the panel which attribute to visualize.

setAttributeColor(SyntaxDocument.ATTR_TYPE, Color) - Method in class weka.gui.scripting.SyntaxDocument

Sets the foreground (font) color of the specified attribute.

setAttributeColor(MutableAttributeSet, Color) - Static method in class weka.gui.scripting.SyntaxDocument

Sets the foreground (font) color of the specified attribute.

setAttributeFont(SyntaxDocument.ATTR_TYPE, int) - Method in class weka.gui.scripting.SyntaxDocument

Sets the font of the specified attribute.

setAttributeFont(MutableAttributeSet, Font) - Static method in class weka.gui.scripting.SyntaxDocument

Sets the font of the specified attribute.

setAttributeID(int) - Method in class weka.experiment.ClassifierSplitEvaluator

Set the index of Attibute Identifying the instances

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.Add

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.AddNoise

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.AddValues

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Sets the index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Sets index of the attribute used.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Sets index of the attribute used.

setAttributeIndexes(String) - Method in class weka.filters.unsupervised.attribute.NominalToString

Sets index of the attribute used.

setAttributeIndices(String) - Method in interface weka.core.DistanceFunction

Sets the range of attributes to use in the calculation of the distance.

setAttributeIndices(String) - Method in class weka.core.NormalizableDistance

Sets the range of attributes to use in the calculation of the distance.

setAttributeIndices(String) - Method in class weka.filters.supervised.attribute.Discretize

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setAttributeIndices(String) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Set which attributes are to be acted on (or not, if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Copy

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.FirstOrder

Set which attributes are to be deleted (or kept if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Set which attributes are to be acted on (or not, if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Sets which attributes are to be acted on.

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Sets the columns to use, e.g., first-last or first-3,5-last

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Sets which attributes are to be "nominalized" (only numeric attributes among the selection will be transformed).

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Set which attributes are to be transformed (or kept if invert is true).

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Remove

Set which attributes are to be deleted (or kept if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Sets which attributes are to be acted on.

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Reorder

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.SortLabels

Set the range of attributes to process.

setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets which attributes are to be worked on.

setAttributeIndicesArray(int[]) - Method in class weka.filters.supervised.attribute.Discretize

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setAttributeIndicesArray(int[]) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Set which attributes are to be acted on (or not, if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Copy

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder

Set which attributes are to be deleted (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Set which attributes are to be acted on (or not, if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Sets which attributes are to be transoformed to nominal.

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Set which attributes are to be transformed (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Remove

Set which attributes are to be deleted (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Reorder

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets which attributes are to be processed.

setAttributeName(String) - Method in class weka.filters.unsupervised.attribute.Add

Set the new attribute's name.

setAttributeName(String) - Method in class weka.filters.unsupervised.attribute.AddID

Set the new attribute's name

setAttributeNamePrefix(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Set the attribute name prefix.

setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.StringToNominal

Sets range of indices of the attributes used.

setAttributes(String) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the range of attributes to output.

setAttributes(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Set the list of attributes to consider for replacing missing values

setAttributeSelectionMethod(SelectedTag) - Method in class weka.classifiers.functions.LinearRegression

Sets the method used to select attributes for use in the linear regression.

setAttributeSpecs(List<AddUserFields.AttributeSpec>) - Method in class weka.filters.unsupervised.attribute.AddUserFields

Set the list of attribute specs to use to create the new attributes.

setAttributeType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.Add

Sets the type of attribute to generate.

setAttributeType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RemoveType

Sets the attribute type to be deleted by the filter.

setAttributeTypes(Hashtable) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Sets the attribute - attribute-type relation to use.

setAttrIndexRange(String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets which attributes are used in the cluster attributes among the selection will be discretized.

setAttsToApplyTo(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Set the attributes to apply the rule to

setAttsToApplyTo(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Set the attributes to apply the rule to

setAutoBuild(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

This will set whether the network is automatically built or if it is left up to the user.

setAutoKeyGeneration(boolean) - Method in class weka.core.converters.DatabaseSaver

En/Dis-ables the automatic generation of a primary key.

setAvgNumberOfItemsPerTA(Double) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the avgNumberOfItemsPerTA property.

setAvgNumberOfItemsPerTransaction(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the avgNumberOfItemsPerTransaction property.

setAvgNumberOfTAsPerTAGroup(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the avgNumberOfTAsPerTAGroup property.

setBackground(Color) - Method in class weka.gui.visualize.BMPWriter

sets the background color to use in creating the BMP.

setBackground(Color) - Method in class weka.gui.visualize.JPEGWriter

sets the background color to use in creating the JPEG.

setBackground(Color) - Method in class weka.gui.visualize.PNGWriter

sets the background color to use in creating the PNG.

setBackground(Color) - Method in class weka.gui.visualize.PostscriptGraphics

setBackgroundColor(Color) - Method in class weka.gui.scripting.SyntaxDocument

Sets the background color.

setBagSizePercent(int) - Method in class weka.classifiers.meta.Bagging

Sets the size of each bag, as a percentage of the training set size.

setBalanceClass(boolean) - Method in class weka.datagenerators.classifiers.classification.Agrawal

Sets whether the class is balanced.

setBallSplitter(BallSplitter) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Sets the ball splitting algorithm to be used by the TopDown constructor.

setBallTreeConstructor(BallTreeConstructor) - Method in class weka.core.neighboursearch.BallTree

Sets the BallTreeConstructor for building the BallTree (default TopDownConstructor).

setBase(double) - Method in class weka.core.neighboursearch.CoverTree

Sets the base to use for expansion constant.

setBaseEvaluation(Evaluation) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

Set the base evaluation object to use.

setBaseExperiment(Experiment) - Method in class weka.experiment.RemoteExperiment

Set the base experiment.

setBaseline(Baseline) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the baseline property.

setBaselineMethod(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the baselineMethod property.

setBaselineModel(BaselineModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the baselineModel property.

setBaselineScore(Double) - Method in class weka.core.pmml.jaxbbindings.Characteristic

Sets the value of the baselineScore property.

setBaselineScore(Double) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the baselineScore property.

setBaselineStrataVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the baselineStrataVariable property.

setBatchSize(String) - Method in interface weka.core.BatchPredictor

Set the batch size to use.

setBeanContext(BeanContext) - Method in class weka.gui.beans.AbstractDataSource

Set a bean context for this bean

setBeanContext(BeanContext) - Method in class weka.gui.beans.CostBenefitAnalysis

setBeanContext(BeanContext) - Method in class weka.gui.beans.DataVisualizer

Set a bean context for this bean

setBeanContext(BeanContext) - Method in class weka.gui.beans.GraphViewer

Set a bean context for this bean

setBeanContext(BeanContext) - Method in class weka.gui.beans.Loader

Set a bean context for this bean

setBeanContext(BeanContext) - Method in class weka.gui.beans.ModelPerformanceChart

Set a bean context for this bean

setBeanContext(BeanContext) - Method in class weka.gui.beans.TextViewer

Set a bean context for this bean

setBeanInstances(Vector<Object>, JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance

Adds the supplied collection of beans at the supplied index in the list of collections.

setBestFit(TIMESERIESALGORITHM) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Sets the value of the bestFit property.

setBeta(double) - Method in class weka.core.pmml.jaxbbindings.PCell

Sets the value of the beta property.

setBias(double) - Method in class weka.classifiers.functions.SGDText

setBias(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron

Sets the value of the bias property.

setBiasToUniformClass(double) - Method in class weka.filters.supervised.instance.Resample

Sets the bias towards a uniform class.

setBIC(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the bic property.

setBIFFile(String) - Method in class weka.classifiers.bayes.BayesNet

Set name of network in BIF file to compare with

setBIFFile(String) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Set name of network in BIF file to read structure from

setBinarizeNumericAttributes(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval

Binarize numeric attributes.

setBinaryAttributesNominal(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary

Sets if binary attributes are to be treates as nominal ones.

setBinaryAttributesNominal(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Sets if binary attributes are to be treates as nominal ones.

setBinarySimilarity(BinarySimilarity) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the binarySimilarity property.

setBinarySplits(boolean) - Method in class weka.classifiers.rules.PART

Set the value of binarySplits.

setBinarySplits(boolean) - Method in class weka.classifiers.trees.J48

Set the value of binarySplits.

setBinRangePrecision(int) - Method in class weka.filters.supervised.attribute.Discretize

Set the precision for bin boundaries.

setBins(int) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets the number of bins to divide each selected numeric attribute into

setBins(int) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Ignored

setBinValue(String) - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin

Sets the value of the binValue property.

setBlendFactor(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Set the blending factor

setBlendMethod(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Set the blending method

setBlockEnd(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the string that is the end of a block.

setBlockOnLastFold(boolean) - Method in class weka.gui.beans.Classifier

Set whether to block on receiving the last fold of the last run rather than rejecting any further data until all processing is complete.

setBlockStart(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the string that is the start of a block.

setBooleanCols(Range) - Method in class weka.datagenerators.ClusterGenerator

Sets which attributes are boolean.

setBooleanIndices(String) - Method in class weka.datagenerators.ClusterGenerator

Sets which attributes are boolean

setBooleanOperator(String) - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate

Sets the value of the booleanOperator property.

setBooleanOperator(String) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Sets the value of the booleanOperator property.

setBoundaryValueMeans(BoundaryValueMeans) - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Sets the value of the boundaryValueMeans property.

setBoundaryValues(BoundaryValues) - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Sets the value of the boundaryValues property.

setBoundaryValues(BoundaryValues) - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Sets the value of the boundaryValues property.

setBuffer(StringBuffer) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the buffer to use.

setBufferSize(int) - Method in class weka.core.converters.CSVLoader

Set the buffer size to use - i.e.

setBufferSize(String) - Method in class weka.gui.beans.Sorter

Set the size of the in-memory buffer

setBuildLogisticModels(boolean) - Method in class weka.classifiers.functions.SMO

Set the value of buildLogisticModels.

setBuildRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.M5Base

Set the value of regressionTree.

setBusinessProblem(String) - Method in class weka.core.pmml.jaxbbindings.Decisions

Sets the value of the businessProblem property.

setC(double) - Method in class weka.classifiers.functions.SMO

Set the value of C.

setC(double) - Method in class weka.classifiers.functions.SMOreg

Set the value of C.

setC00Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the c00Parameter property.

setC01Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the c01Parameter property.

setC10Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the c10Parameter property.

setC11Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the c11Parameter property.

setCacheKeyName(String) - Method in class weka.experiment.DatabaseResultListener

Set the value of CacheKeyName.

setCacheSize(int) - Method in class weka.classifiers.functions.supportVector.CachedKernel

Sets the size of the cache to use (a prime number)

setCacheSize(int) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets the size of the cache to use (a prime number)

setCalcOutOfBag(boolean) - Method in class weka.classifiers.meta.Bagging

Set whether the out of bag error is calculated.

setCalculateStdDevs(boolean) - Method in class weka.experiment.AveragingResultProducer

Set the value of CalculateStdDevs.

setCanChangeClassInDialog(boolean) - Method in class weka.gui.GenericObjectEditor

Sets whether the user can change the class in the dialog.

setCanopies(Instances) - Method in class weka.clusterers.Canopy

Set the canopies to use (replaces any learned by this clusterer already)

setCanopyMaxNumCanopiesToHoldInMemory(int) - Method in class weka.clusterers.SimpleKMeans

Set the maximum number of candidate canopies to retain in memory during training.

setCanopyMinimumCanopyDensity(double) - Method in class weka.clusterers.SimpleKMeans

Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.

setCanopyPeriodicPruningRate(int) - Method in class weka.clusterers.SimpleKMeans

Set the how often to prune low density canopies during training (if using canopy clustering)

setCanopyT1(double) - Method in class weka.clusterers.SimpleKMeans

Set the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

setCanopyT2(double) - Method in class weka.clusterers.SimpleKMeans

Set the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

setCapabilities(Capabilities) - Method in class weka.core.FindWithCapabilities

Uses the given Capabilities for the search.

setCapabilities(Capabilities) - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

sets the initial capabilities.

setCapabilitiesFilter(Capabilities) - Method in class weka.gui.ConverterFileChooser

sets the capabilities that the savers must have.

setCapabilitiesFilter(Capabilities) - Method in class weka.gui.GenericObjectEditor

Sets the capabilities to use for filtering.

setCapacity(int) - Method in class weka.core.FastVector

Deprecated. Sets the vector's capacity to the given value.

setCapacity(int) - Method in class weka.core.matrix.DoubleVector

Sets the capacity of the vector

setCapacity(int) - Method in class weka.core.matrix.IntVector

Sets the capacity of the vector

setCar(boolean) - Method in class weka.associations.Apriori

Sets class association rule mining

setCardinality(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Counts

Sets the value of the cardinality property.

setCardinality(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet

Sets the cardinality of the attributes (incl class attribute)

setCaseSensitive(boolean) - Method in class weka.gui.scripting.SyntaxDocument

Sets whether the keywords are case-sensitive or not.

setCastInteger(String) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the castInteger property.

setCategoricalScoringMethod(CATSCORINGMETHOD) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the categoricalScoringMethod property.

setCategories(Categories) - Method in class weka.core.pmml.jaxbbindings.Predictor

Sets the value of the categories property.

setCategory(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the category property.

setCell(int, int, Object) - Method in class weka.classifiers.CostMatrix

Set the value of a particular cell in the matrix

setCenter(double) - Method in class weka.gui.treevisualizer.Node

Set the value of center.

setCenterData(boolean) - Method in class weka.attributeSelection.PrincipalComponents

Set whether to center (rather than standardize) the data.

setCenterData(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Set whether to center (rather than standardize) the data.

setCenteredLocation() - Method in class weka.gui.arffviewer.ArffViewer

positions the window at the center of the screen

setChanged(boolean) - Method in class weka.gui.arffviewer.ArffPanel

can only reset the changed state to FALSE

setChar(Character) - Method in class weka.core.Trie.TrieNode

sets the character this node represents

setCharSet(String) - Method in class weka.core.converters.TextDirectoryLoader

Set the character set to use when reading text files (an empty string indicates that the default character set will be used).

setChartingEvalWindowSize(int) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Set whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).

setChebychev(Chebychev) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the chebychev property.

setChecked(int, boolean) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

sets the checked state of the element at the given index

setChecked(int, boolean) - Method in class weka.gui.CheckBoxList

sets the checked state of the element at the given index

setCheckErrorRate(boolean) - Method in class weka.classifiers.rules.JRip

Sets whether to check for error rate is in stopping criterion

setChecksTurnedOff(boolean) - Method in class weka.classifiers.functions.SMO

Disables or enables the checks (which could be time-consuming).

setChecksTurnedOff(boolean) - Method in class weka.classifiers.functions.supportVector.Kernel

Disables or enables the checks (which could be time-consuming).

setChecksTurnedOff(boolean) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Disables or enables the checks (which could be time-consuming).

setChild(String, HNode) - Method in class weka.classifiers.trees.ht.SplitNode

Add a child

setChildField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the childField property.

setChiSquareValue(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the chiSquareValue property.

setCindex(int, double, double) - Method in class weka.gui.visualize.AttributePanel

Set the index of the attribute by which to colour the data.

setCindex(int) - Method in class weka.gui.visualize.AttributePanel

Set the index of the attribute by which to colour the data.

setCindex(int) - Method in class weka.gui.visualize.ClassPanel

Set the index of the attribute to display coloured labels for

setCindex(int) - Method in class weka.gui.visualize.Plot2D

Set the index of the attribute to use for colouring

setCindex(int) - Method in class weka.gui.visualize.PlotData2D

Set the colouring index of the data

setCityBlock(CityBlock) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the cityBlock property.

setClass(Attribute) - Method in class weka.core.Instances

Sets the class attribute.

setClassColumn(String) - Method in class weka.gui.beans.ClassAssigner

setClassFlag(boolean) - Method in class weka.datagenerators.ClusterGenerator

Sets the class flag, if class flag is set, the cluster is listed as class atrribute in an extra attribute.

setClassForIRStatistics(int) - Method in class weka.experiment.ClassifierSplitEvaluator

Set the value of ClassForIRStatistics.

setClassificationMethod(SVMCLASSIFICATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the classificationMethod property.

setClassifier(Classifier) - Method in class weka.attributeSelection.WrapperSubsetEval

Set the classifier to use for accuracy estimation

setClassifier(Classifier) - Method in class weka.classifiers.BVDecompose

Set the classifiers being analysed

setClassifier(Classifier) - Method in class weka.classifiers.BVDecomposeSegCVSub

Set the classifiers being analysed

setClassifier(Classifier) - Method in class weka.classifiers.CheckClassifier

Set the classifier for boosting.

setClassifier(Classifier) - Method in class weka.classifiers.CheckSource

Sets the classifier to use for the comparison.

setClassifier(Classifier) - Method in class weka.classifiers.SingleClassifierEnhancer

Set the base learner.

setClassifier(Classifier) - Method in class weka.experiment.ClassifierSplitEvaluator

Sets the classifier.

setClassifier(Classifier) - Method in class weka.experiment.RegressionSplitEvaluator

Sets the classifier.

setClassifier(Classifier) - Method in class weka.filters.supervised.attribute.AddClassification

Sets the classifier to classify instances with.

setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the classifier to classify instances with.

setClassifier(Classifier) - Method in class weka.gui.beans.BatchClassifierEvent

Set the classifier

setClassifier(Classifier) - Method in class weka.gui.beans.IncrementalClassifierEvent

setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the classifier to use.

setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Set a classifier to use

setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the classifier to use

setClassifier(Classifier) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Sets the classifier used for making the predictions.

setClassifierName(String) - Method in class weka.experiment.ClassifierSplitEvaluator

Set the Classifier to use, given it's class name.

setClassifierName(String) - Method in class weka.experiment.RegressionSplitEvaluator

Set the Classifier to use, given it's class name.

setClassifierPanel(ClassifierPanel) - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin

Allows the classifier panel to pass in a reference to itself

setClassifiers(Classifier[]) - Method in class weka.classifiers.meta.MultiScheme

Sets the list of possible classifers to choose from.

setClassifiers(Classifier[]) - Method in class weka.classifiers.MultipleClassifiersCombiner

Sets the list of possible classifers to choose from.

setClassifierTemplate(Classifier) - Method in class weka.gui.beans.Classifier

Set the template classifier for this wrapper

setClassifyIterations(int) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets the number of times an instance is classified

setClassIndex(int) - Method in class weka.associations.Apriori

Sets the class index

setClassIndex(int) - Method in interface weka.associations.CARuleMiner

Sets the class index for the class association rule miner

setClassIndex(int) - Method in class weka.associations.FilteredAssociator

Sets the class index

setClassIndex(int) - Method in class weka.classifiers.BVDecompose

Sets index of attribute to discretize on

setClassIndex(int) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets index of attribute to discretize on

setClassIndex(int) - Method in class weka.classifiers.CheckSource

Sets the class index of the dataset.

setClassIndex(String) - Method in class weka.core.converters.JSONSaver

Sets index of the class attribute.

setClassIndex(String) - Method in class weka.core.converters.LibSVMSaver

Sets index of the class attribute.

setClassIndex(String) - Method in class weka.core.converters.SVMLightSaver

Sets index of the class attribute.

setClassIndex(String) - Method in class weka.core.converters.XRFFSaver

Sets index of the class attribute.

setClassIndex(String) - Method in class weka.core.FindWithCapabilities

sets the class index, -1 for none, first and last are also valid.

setClassIndex(int) - Method in class weka.core.Instances

Sets the class index of the set.

setClassIndex(int) - Method in class weka.core.TestInstances

sets the class index (0-based)

setClassIndex(int) - Method in class weka.filters.CheckSource

Sets the class index of the dataset.

setClassIndex(String) - Method in class weka.filters.unsupervised.attribute.ClassAssigner

sets the class index.

setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the attribute on which misclassifications are based.

setClassIndex(int) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Sets the 0-based class index.

setClassLabels(ClassLabels) - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix

Sets the value of the classLabels property.

setClassMissing() - Method in class weka.core.AbstractInstance

Sets the class value of an instance to be "missing".

setClassMissing() - Method in interface weka.core.Instance

Sets the class value of an instance to be "missing".

setClassname(String) - Method in class weka.core.AllJavadoc

sets the classname of the class to generate the Javadoc for

setClassname(String) - Method in class weka.core.Javadoc

sets the classname of the class to generate the Javadoc for

setClassname(String) - Method in class weka.core.ListOptions

sets the classname of the class to generate the Javadoc for

setClassName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Sets the class containing the transformation method.

setClassOrder(int) - Method in class weka.filters.supervised.attribute.ClassOrder

Set the wanted class order

setClassType(int) - Method in class weka.core.TestInstances

sets the class attribute type

setClassType(Class<?>) - Method in class weka.gui.GenericObjectEditor

Sets the class of values that can be edited.

setClassValue(double) - Method in class weka.core.AbstractInstance

Sets the class value of an instance to the given value (internal floating-point format).

setClassValue(String) - Method in class weka.core.AbstractInstance

Sets the class value of an instance to the given value.

setClassValue(double) - Method in interface weka.core.Instance

Sets the class value of an instance to the given value (internal floating-point format).

setClassValue(String) - Method in interface weka.core.Instance

Sets the class value of an instance to the given value.

setClassValue(String) - Method in class weka.gui.beans.ClassValuePicker

Set the class value considered to be the "positive" class value.

setClassValueIndex(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Set the class value index to use

setClearEachDataset(boolean) - Method in class weka.gui.streams.InstanceViewer

setClip(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

setClip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

setCloseTo(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the "close to" number.

setCloseToDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the "close to" default.

setCloseToTolerance(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the "close to" Tolerance.

setClosure(String) - Method in class weka.core.pmml.jaxbbindings.Interval

Sets the value of the closure property.

setClusterCanopyAssignments(List<long[]>) - Method in class weka.clusterers.Canopy

Set the canopies that each canopy (cluster center) is within T1 distance of

setClusterDefinitions(ClusterDefinition[]) - Method in class weka.datagenerators.clusterers.SubspaceCluster

sets the clusters to use

setClusterer(Clusterer) - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator

Set the clusterer to use

setClusterer(Clusterer) - Method in class weka.clusterers.CheckClusterer

Set the clusterer for testing.

setClusterer(Clusterer) - Method in class weka.clusterers.ClusterEvaluation

set the clusterer

setClusterer(Clusterer) - Method in class weka.clusterers.MakeDensityBasedClusterer

Sets the clusterer to wrap.

setClusterer(Clusterer) - Method in class weka.clusterers.SingleClustererEnhancer

Set the base clusterer.

setClusterer(DensityBasedClusterer) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Sets the clusterer.

setClusterer(Clusterer) - Method in class weka.filters.unsupervised.attribute.AddCluster

Sets the clusterer to assign clusters with.

setClusterer(Clusterer) - Method in class weka.gui.beans.Clusterer

Set the clusterer for this wrapper

setClusterer(Clusterer) - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances

Sets the classifier used for making the predictions.

setClustererName(String) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Set the Clusterer to use, given it's class name.

setClustererPanel(ClustererPanel) - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin

Allows the clusterer panel to pass in a reference to itself

setClusterEvaluation(ClusterEvaluation) - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances

Sets the cluster evaluation object to use.

setClusteringModel(ClusteringModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the clusteringModel property.

setClusterSubType(SelectedTag) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the cluster sub type.

setClusterType(SelectedTag) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the cluster type.

setCoef0(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Sets the value of the coef0 property.

setCoef0(Double) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Sets the value of the coef0 property.

setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Sets the value of the coefficient property.

setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Sets the value of the coefficient property.

setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Sets the value of the coefficient property.

setCoefficients(Coefficients) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Sets the value of the coefficients property.

setCol(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MatCell

Sets the value of the col property.

setColHidden(int, boolean) - Method in class weka.experiment.ResultMatrix

sets the hidden status of the column (if the index is valid).

setCollapseTree(boolean) - Method in class weka.classifiers.trees.J48

Set the value of collapseTree.

setColName(int, String) - Method in class weka.experiment.ResultMatrix

sets the name of the column (if the index is valid).

setColNameWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the column names (0 = optimal).

setColor(Color) - Method in class weka.gui.treevisualizer.Node

Set the value of color.

setColor(Color) - Method in class weka.gui.visualize.PostscriptGraphics

Set current pen color.

setColOrder(int[]) - Method in class weka.experiment.ResultMatrix

sets the ordering of the columns, null means default.

setColoringIndex(int) - Method in class weka.gui.AttributeVisualizationPanel

Set the coloring (class) index for the plot

setColoringIndex(int) - Method in class weka.gui.beans.AttributeSummarizer

Set the coloring index for the attribute summary plots

setColors(ArrayList<Color>) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set a vector of Color objects for the classes

setColourIndex(int) - Method in class weka.gui.visualize.VisualizePanel

Sets the index used for colouring.

setColours(ArrayList<Color>) - Method in class weka.gui.visualize.AttributePanel

Sets a list of colours to use for colouring data points

setColours(ArrayList<Color>) - Method in class weka.gui.visualize.ClassPanel

Set a list of colours to use for colouring labels

setColours(ArrayList<Color>) - Method in class weka.gui.visualize.Plot2D

Set a list of colours to use when colouring points according to class values or cluster numbers

setColumn(int, double[]) - Method in class weka.core.Matrix

Deprecated. Sets a column of the matrix to the given column.

setColumn(String) - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair

Sets the value of the column property.

setColumn(String) - Method in class weka.core.pmml.jaxbbindings.InstanceField

Sets the value of the column property.

setColumn(String) - Method in class weka.core.pmml.jaxbbindings.VerificationField

Sets the value of the column property.

setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.Vote

Sets the combination rule to use.

setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the compareFunction property.

setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the compareFunction property.

setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.KNNInput

Sets the value of the compareFunction property.

setComparisons(Comparisons) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the comparisons property.

setComponent(JComponent) - Method in class weka.gui.visualize.JComponentWriter

sets the component to print to an output format

setComposite(Composite) - Method in class weka.gui.visualize.PostscriptGraphics

setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the compoundPredicate property.

setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Sets the value of the compoundPredicate property.

setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the compoundPredicate property.

setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the compoundPredicate property.

setCompressOutput(boolean) - Method in class weka.core.converters.ArffSaver

Sets whether to compress the output.

setCompressOutput(boolean) - Method in class weka.core.converters.JSONSaver

Sets whether to compress the output.

setCompressOutput(boolean) - Method in class weka.core.converters.XRFFSaver

Sets whether to compress the output.

setConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the confidence property.

setConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Sets the value of the confidence property.

setConfidence(double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the confidence property.

setConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the confidence property.

setConfidenceFactor(float) - Method in class weka.classifiers.rules.PART

Set the value of CF.

setConfidenceFactor(float) - Method in class weka.classifiers.trees.J48

Set the value of CF.

setConfidenceLevel(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the confidenceLevel property.

setConfidenceLowerBound(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the confidenceLowerBound property.

setConfidenceUpperBound(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the confidenceUpperBound property.

setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewer

whether to present a MessageBox on Exit or not

setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

whether to present a MessageBox on Exit or not

setConfusionMatrix(ConfusionMatrix) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the confusionMatrix property.

setConnections(Vector<BeanConnection>, Integer...) - Static method in class weka.gui.beans.BeanConnection

Describe setConnections method here.

setConnectPoints(boolean[]) - Method in class weka.gui.visualize.PlotData2D

Set whether consecutive points should be connected by lines

setConnectPoints(ArrayList<Boolean>) - Method in class weka.gui.visualize.PlotData2D

Set whether consecutive points should be connected by lines

setConsequent(double) - Method in class weka.classifiers.rules.JRip.RipperRule

Sets the internal representation of the class label to be predicted

setConsequent(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the consequent property.

setConservativeForwardSelection(boolean) - Method in class weka.attributeSelection.GreedyStepwise

Set whether attributes should continue to be added during a forward search as long as merit does not decrease

setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the constant property.

setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the constant property.

setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the constant property.

setConsumeNonMatching(boolean) - Method in class weka.gui.beans.SubstringLabeler

Set whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.

setConsumeNonMatching(boolean) - Method in class weka.gui.beans.SubstringLabelerRules

Set whether to consume non matching instances.

setContainChildBalls(boolean) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets whether if a parent ball should completely enclose its two child balls.

setContent(String) - Method in class weka.core.pmml.jaxbbindings.ArrayType

Sets the value of the content property.

setContent(String) - Method in class weka.gui.scripting.Script

Sets the content.

setContentType(String) - Method in class weka.gui.DocumentPrinting

Sets the content type.

setContinuousScoringMethod(CONTSCORINGMETHOD) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the continuousScoringMethod property.

setContrastMatrixType(String) - Method in class weka.core.pmml.jaxbbindings.Predictor

Sets the value of the contrastMatrixType property.

setContStats(ContStats) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the contStats property.

setConvertNominal(boolean) - Method in class weka.classifiers.trees.LMT

Set the value of convertNominal.

setCoord1(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Sets the value of the coord1 property.

setCoord2(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Sets the value of the coord2 property.

setCoord3(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap

Sets the value of the coord3 property.

setCopyright(String) - Method in class weka.core.pmml.jaxbbindings.Header

Sets the value of the copyright property.

setCoreConvertersOnly(boolean) - Method in class weka.gui.ConverterFileChooser

Whether to display only the hardocded core converters.

setCorrelationFields(CorrelationFields) - Method in class weka.core.pmml.jaxbbindings.Correlations

Sets the value of the correlationFields property.

setCorrelationMethods(CorrelationMethods) - Method in class weka.core.pmml.jaxbbindings.Correlations

Sets the value of the correlationMethods property.

setCorrelations(Correlations) - Method in class weka.core.pmml.jaxbbindings.ModelExplanation

Sets the value of the correlations property.

setCorrelationValues(CorrelationValues) - Method in class weka.core.pmml.jaxbbindings.Correlations

Sets the value of the correlationValues property.

setCostMatrix(CostMatrix) - Method in class weka.classifiers.meta.CostSensitiveClassifier

Sets the misclassification cost matrix.

setCostMatrixSource(SelectedTag) - Method in class weka.classifiers.meta.CostSensitiveClassifier

Sets the source location of the cost matrix.

setCount(double) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Sets the value of the count property.

setCount(double) - Method in class weka.core.pmml.jaxbbindings.TargetValueCount

Sets the value of the count property.

setCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeException

Sets the value of the count property.

setCount(int, double) - Method in class weka.experiment.ResultMatrix

sets the count for the row (if the index is valid).

setCounter(int) - Method in class weka.associations.ItemSet

Sets the counter

setCounts(Counts) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Sets the value of the counts property.

setCounts(Counts) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the counts property.

setCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the countTable property.

setCountWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the counts (0 = optimal).

setCovariances(Covariances) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the covariances property.

setCreatorApplication(Document) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Set the name of the application (if specified) that created this model

setCreatorApplication(Document) - Method in interface weka.core.pmml.PMMLModel

Set the name of the application (if specified) that created this.

setCriterion(String) - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod

Sets the value of the criterion property.

setCrossVal(int) - Method in class weka.classifiers.rules.DecisionTable

Sets the number of folds for cross validation (1 = leave one out)

setCrossValidate(boolean) - Method in class weka.classifiers.lazy.IBk

Sets whether hold-one-out cross-validation will be used to select the best k value.

setCumHazard(double) - Method in class weka.core.pmml.jaxbbindings.BaselineCell

Sets the value of the cumHazard property.

setCumulativeLink(CUMULATIVELINKFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the cumulativeLink property.

setCurrentFilename(String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

sets the filename of the current tab

setCurrentInstance(Instance) - Method in class weka.gui.beans.IncrementalClassifierEvent

Set the current instance for this event

setCurrentZoomSetting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setCurveData(PlotData2D, Attribute) - Method in class weka.gui.beans.CostBenefitAnalysis

Set the threshold curve data to use.

setCustomColour(Color) - Method in class weka.gui.visualize.PlotData2D

Set a custom colour to use for this plot.

setCustomHeight(int) - Method in class weka.gui.visualize.JComponentWriter

sets the custom height to use

setCustomName(String) - Method in class weka.gui.beans.Appender

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Associator

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in interface weka.gui.beans.BeanCommon

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.ClassAssigner

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Classifier

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.ClassValuePicker

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Clusterer

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.CostBenefitAnalysis

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.CrossValidationFoldMaker

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.DataVisualizer

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Filter

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.FlowByExpression

setCustomName(String) - Method in class weka.gui.beans.ImageSaver

setCustomName(String) - Method in class weka.gui.beans.ImageViewer

setCustomName(String) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Join

Set a custom name for this step

setCustomName(String) - Method in class weka.gui.beans.Loader

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.MetaBean

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.PredictionAppender

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Saver

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.SerializedModelSaver

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.Sorter

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.StripChart

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.SubstringLabeler

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.SubstringReplacer

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.TestSetMaker

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.TextSaver

setCustomName(String) - Method in class weka.gui.beans.TextViewer

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.TrainingSetMaker

Set a custom (descriptive) name for this bean

setCustomName(String) - Method in class weka.gui.beans.TrainTestSplitMaker

Set a custom (descriptive) name for this bean

setCustomPropsFile(File) - Method in class weka.core.converters.DatabaseLoader

Sets the custom properties file to use.

setCustomPropsFile(File) - Method in class weka.core.converters.DatabaseSaver

Sets the custom properties file to use.

setCustomPropsFile(File) - Method in class weka.experiment.InstanceQuery

Sets the custom properties file to use.

setCustomWidth(int) - Method in class weka.gui.visualize.JComponentWriter

sets the custom width to use

setCutoff(double) - Method in class weka.clusterers.Cobweb

set the cutoff

setCVisible(boolean) - Method in class weka.gui.treevisualizer.Node

Sets all the children of this node either to visible or invisible

setCVParameters(Object[]) - Method in class weka.classifiers.meta.CVParameterSelection

Set method for CVParameters.

setCVType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

set cross validation strategy to be used in searching for networks.

setD00Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the d00Parameter property.

setD01Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the d01Parameter property.

setD10Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the d10Parameter property.

setD11Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity

Sets the value of the d11Parameter property.

setData(Instances) - Method in class weka.classifiers.bayes.net.EditableBayesNet

Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.

setData(Instances) - Method in class weka.classifiers.rules.RuleStats

Set the data of the stats, overwriting the old one if any

setDatabaseURL(String) - Method in class weka.experiment.DatabaseUtils

Set the value of DatabaseURL.

setDataDictionary(DataDictionary) - Method in class weka.core.pmml.jaxbbindings.PMML

Sets the value of the dataDictionary property.

setDataFileName(String) - Method in class weka.classifiers.BVDecompose

Sets the name of the data file used for the decomposition

setDataFileName(String) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets the name of the dataset file.

setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the data generator to use for generating new instances

setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the density estimator to use

setDataName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Sets the value of the dataName property.

setDataName(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the dataName property.

setDataPoint(double[]) - Method in class weka.gui.beans.ChartEvent

Set the data point

setDataset(File) - Method in class weka.classifiers.CheckSource

Sets the dataset to use for testing.

setDataset(Instances) - Method in class weka.core.AbstractInstance

Sets the reference to the dataset.

setDataset(Instances) - Method in interface weka.core.Instance

Sets the reference to the dataset.

setDataset(File) - Method in class weka.filters.CheckSource

Sets the dataset to use for testing.

setDatasetFormat(Instances) - Method in class weka.datagenerators.DataGenerator

Sets the format of the dataset that is to be generated.

setDatasetKeyColumns(Range) - Method in class weka.experiment.PairedTTester

Set the value of DatasetKeyColumns.

setDatasetKeyColumns(Range) - Method in interface weka.experiment.Tester

Set the value of DatasetKeyColumns.

setDatasetKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel

setDatasets(DefaultListModel) - Method in class weka.experiment.Experiment

Set the datasets to use in the experiment

setDatasets(DefaultListModel) - Method in class weka.experiment.RemoteExperiment

Set the datasets to use in the experiment

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.Constant

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.Discretize

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.ParameterField

Sets the value of the dataType property.

setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the dataType property.

setDataType(int) - Method in class weka.gui.beans.xml.XMLBeans

sets what kind of data is to be read/written

setDataUsage(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the dataUsage property.

setDateAttributes(String) - Method in class weka.core.converters.CSVLoader

Set the attribute range to be forced to type date.

setDateFormat(String) - Method in class weka.core.converters.CSVLoader

Set the format to use for parsing date values.

setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.Add

Set the date format, complying to ISO-8601.

setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Sets the output date format.

setDateFormat(SimpleDateFormat) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Sets the output date format.

setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Set the date format to use for parsing the date replacement constant

setDateReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Set the date replacement value

setDB(boolean) - Method in class weka.gui.beans.Loader

setDebug(boolean) - Method in class weka.attributeSelection.CfsSubsetEval

Set whether to output debugging info

setDebug(boolean) - Method in class weka.classifiers.AbstractClassifier

Set debugging mode.

setDebug(boolean) - Method in class weka.classifiers.BVDecompose

Sets debugging mode

setDebug(boolean) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets debugging mode

setDebug(boolean) - Method in class weka.classifiers.functions.Logistic

Sets whether debugging output will be printed.

setDebug(boolean) - Method in class weka.classifiers.functions.supportVector.Kernel

Enables or disables the output of debug information (if the derived kernel supports that)

setDebug(boolean) - Method in class weka.classifiers.meta.MultiScheme

Set debugging mode

setDebug(boolean) - Method in class weka.classifiers.rules.JRip

Sets whether debug information is output to the console

setDebug(boolean) - Method in class weka.clusterers.AbstractClusterer

Set debugging mode.

setDebug(boolean) - Method in class weka.clusterers.EM

Set debug mode - verbose output

setDebug(boolean) - Method in class weka.core.Check

Set debugging mode

setDebug(boolean) - Method in class weka.core.converters.TextDirectoryLoader

Sets whether to print some debug information.

setDebug(boolean) - Method in class weka.core.Debug.Random

sets whether to print the generated random values or not

setDebug(boolean) - Method in class weka.core.Optimization

Set whether in debug mode

setDebug(boolean) - Method in class weka.datagenerators.DataGenerator

Sets the debug flag.

setDebug(boolean) - Method in class weka.estimators.CheckEstimator

Set debugging mode

setDebug(boolean) - Method in class weka.estimators.Estimator

Set debugging mode.

setDebug(boolean) - Method in class weka.experiment.DatabaseUtils

Sets whether there should be printed some debugging output to stderr or not.

setDebug(boolean) - Method in class weka.filters.SimpleFilter

Set debugging mode.

setDebug(boolean) - Method in class weka.filters.unsupervised.attribute.AddExpression

Set debug mode.

setDebug(boolean) - Method in class weka.gui.scripting.ScriptingPanel

Turns on/off debugging mode.

setDebug(boolean) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion

sets debug mode on/off.

setDebug(boolean) - Method in class weka.gui.streams.InstanceCounter

setDebug(boolean) - Method in class weka.gui.streams.InstanceJoiner

setDebug(boolean) - Method in class weka.gui.streams.InstanceLoader

setDebug(boolean) - Method in class weka.gui.streams.InstanceSavePanel

setDebug(boolean) - Method in class weka.gui.streams.InstanceTable

setDebug(boolean) - Method in class weka.gui.streams.InstanceViewer

setDebuggingOutput(boolean) - Method in class weka.attributeSelection.GreedyStepwise

Set whether to output debugging info to the console

setDecay(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

setDecimals(int) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the number of decimals to round to.

setDecisions(Decisions) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the decisions property.

setDefaultChild(String) - Method in class weka.core.pmml.jaxbbindings.Node

Sets the value of the defaultChild property.

setDefaultConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet

Sets the value of the defaultConfidence property.

setDefaultScore(String) - Method in class weka.core.pmml.jaxbbindings.RuleSet

Sets the value of the defaultScore property.

setDefaultValue(String) - Method in class weka.core.pmml.jaxbbindings.Discretize

Sets the value of the defaultValue property.

setDefaultValue(BigInteger) - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Sets the value of the defaultValue property.

setDefaultValue(String) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the defaultValue property.

setDefaultValue(Double) - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Sets the value of the defaultValue property.

setDefaultValue(Double) - Method in class weka.core.pmml.jaxbbindings.TargetValue

Sets the value of the defaultValue property.

setDefaultValue() - Method in class weka.gui.GenericObjectEditor

Sets the current object to be the default, taken as the first item in the chooser.

setDegree(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Sets the value of the degree property.

setDegreesOfFreedom(double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the degreesOfFreedom property.

setDegreesOfFreedom(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the degreesOfFreedom property.

setDegreesOfFreedom(int) - Method in class weka.experiment.PairedStats

Sets the degrees of freedom (if calibration is required).

setDeleteEmptyBins(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization

Sets whether to delete empty bins.

setDelimiter(DELIMITER2) - Method in class weka.core.pmml.jaxbbindings.Delimiter

Sets the value of the delimiter property.

setDelimiters(String) - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer

Set the value of delimiters.

setDelimiters(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the delimiter characters to use.

setDelta(double) - Method in class weka.associations.Apriori

Set the value of delta.

setDelta(double) - Method in class weka.associations.FPGrowth

Set the value of delta.

setDelta(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Sets the m_fDelta.

setDelta(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Sets the m_fDelta.

setDelta(Double) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the delta property.

setDensityBasedClusterer(DensityBasedClusterer) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Set the clusterer for use in filtering

setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.BayesInput

Sets the value of the derivedField property.

setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.NeuralInput

Sets the value of the derivedField property.

setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.NeuralOutput

Sets the value of the derivedField property.

setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Decision

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Decisions

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Header

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.LinearKernelType

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType

Sets the value of the description property.

setDescription(String) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Sets the value of the description property.

setDesign(boolean) - Method in class weka.gui.beans.AttributeSummarizer

Set whether the appearance of this bean should be design or application

setDesiredWeightOfInstancesPerInterval(double) - Method in class weka.filters.unsupervised.attribute.Discretize

Set the DesiredWeightOfInstancesPerInterval value.

setDestination(File) - Method in class weka.core.converters.AbstractFileSaver

Sets the destination file (and directories if necessary).

setDestination(OutputStream) - Method in class weka.core.converters.AbstractFileSaver

Sets the destination output stream.

setDestination(File) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setDestination(OutputStream) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setDestination(OutputStream) - Method in class weka.core.converters.ArffSaver

Sets the destination output stream.

setDestination(String, String, String) - Method in class weka.core.converters.DatabaseSaver

Sets the database url.

setDestination(String) - Method in class weka.core.converters.DatabaseSaver

Sets the database url.

setDestination() - Method in class weka.core.converters.DatabaseSaver

Sets the database url using the DatabaseUtils file.

setDestination(OutputStream) - Method in class weka.core.converters.JSONSaver

Sets the destination output stream.

setDestination(File) - Method in interface weka.core.converters.Saver

Resets the Saver object and sets the destination to be the supplied File object.

setDestination(OutputStream) - Method in interface weka.core.converters.Saver

Resets the Saver object and sets the destination to be the supplied InputStream.

setDestination(OutputStream) - Method in class weka.core.converters.SerializedInstancesSaver

Sets the destination output stream.

setDestination(OutputStream) - Method in class weka.core.converters.XRFFSaver

Sets the destination output stream.

setDetectionPerAttribute(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Set whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").

setDF(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the df property.

setDf(BigInteger) - Method in class weka.core.pmml.jaxbbindings.PCell

Sets the value of the df property.

setDiagDefault(Double) - Method in class weka.core.pmml.jaxbbindings.Matrix

Sets the value of the diagDefault property.

setDir(String) - Method in class weka.core.converters.AbstractFileSaver

Sets the directory where the instances should be stored

setDir(String) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setDir(String) - Method in interface weka.core.converters.Saver

Sets the directory of the output file.

setDir(String) - Method in class weka.core.Javadoc

sets the dir containing the file that is to be updated.

setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractFileSaver

Sets the directory and the file prefix.

setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setDirAndPrefix(String, String) - Method in interface weka.core.converters.Saver

Sets the file prefix and the directory.

setDirection(SelectedTag) - Method in class weka.attributeSelection.BestFirst

Set the search direction

setDirectory(File) - Method in class weka.core.converters.TextDirectoryLoader

sets the source directory

setDirectory(File) - Method in class weka.gui.beans.SerializedModelSaver

Set the directory that the model(s) will be saved into.

setDiscardPredictions(boolean) - Method in class weka.classifiers.evaluation.Evaluation

Sets whether to discard predictions, ie, not storing them for future reference via predictions() method in order to conserve memory.

setDiscardPredictions(boolean) - Method in class weka.classifiers.Evaluation

Sets whether to discard predictions, ie, not storing them for future reference via predictions() method in order to conserve memory.

setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the discretize property.

setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the discretize property.

setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the discretize property.

setDiscrStats(DiscrStats) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the discrStats property.

setDisplayConnectors(boolean) - Method in class weka.gui.beans.BeanVisual

Turn on/off the connector points

setDisplayConnectors(boolean, Color) - Method in class weka.gui.beans.BeanVisual

Turn on/off the connector points

setDisplayedFromDialog() - Method in class weka.gui.experiment.ResultsPanel

setDisplayedResultsets(int[]) - Method in class weka.experiment.PairedTTester

Sets the indicies of the datasets to display (null means all).

setDisplayedResultsets(int[]) - Method in interface weka.experiment.Tester

Sets the indicies of the datasets to display (null means all).

setDisplayModelInOldFormat(boolean) - Method in class weka.classifiers.bayes.NaiveBayes

Set whether to display model output in the old, original format.

setDisplayModelInOldFormat(boolean) - Method in class weka.clusterers.EM

Set whether to display model output in the old, original format.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the displayName property.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the displayName property.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the displayName property.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the displayName property.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Sets the value of the displayName property.

setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Sets the value of the displayName property.

setDisplayRules(boolean) - Method in class weka.classifiers.rules.DecisionTable

Sets whether rules are to be printed

setDisplayStdDevs(boolean) - Method in class weka.clusterers.SimpleKMeans

Sets whether standard deviations and nominal count.

setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.Decision

Sets the value of the displayValue property.

setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValue

Sets the value of the displayValue property.

setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.Value

Sets the value of the displayValue property.

setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.HierarchicalClusterer

setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.SimpleKMeans

sets the distance function to use for instance comparison.

setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.CoverTree

Sets the distance function to use for nearest neighbour search.

setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.KDTree

sets the distance function to use for nearest neighbour search.

setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

sets the distance function to use for nearest neighbour search.

setDistanceIsBranchLength(boolean) - Method in class weka.clusterers.HierarchicalClusterer

setDistanceWeighting(SelectedTag) - Method in class weka.classifiers.lazy.IBk

Sets the distance weighting method used.

setDistMult(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the distance multiplier.

setDistParameter(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the distParameter property.

setDistribution(String, double[][]) - Method in class weka.classifiers.bayes.net.EditableBayesNet

specify distribution of a node

setDistribution(int, double[][]) - Method in class weka.classifiers.bayes.net.EditableBayesNet

specify distribution of a node

setDistribution(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the distribution property.

setDistribution(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets the distribution to use for calculating the random matrix

setDistributionSpread(double) - Method in class weka.filters.supervised.instance.SpreadSubsample

Sets the value for the distribution spread

setDocType(String) - Method in class weka.core.xml.XMLDocument

sets the DOCTYPE-String to use in the XML output.

setDocument(Document) - Method in class weka.core.xml.XMLDocument

sets the DOM document to use.

setDocument(JTextPane) - Method in class weka.gui.DocumentPrinting

Sets the document from the given JTextPane.

setDocument(String, Document) - Method in class weka.gui.DocumentPrinting

Sets the document and the according content type.

setDocumentNormalization(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Sets the value of the documentNormalization property.

setDoNotCheckCapabilities(boolean) - Method in class weka.classifiers.AbstractClassifier

Set whether not to check capabilities.

setDoNotCheckCapabilities(boolean) - Method in class weka.clusterers.AbstractClusterer

Set whether not to check capabilities.

setDoNotCheckCapabilities(boolean) - Method in class weka.filters.SimpleFilter

Set whether not to check capabilities.

setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.rules.PART

Sets the value of doNotMakeSplitPointActualValue.

setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.trees.J48

Sets the value of doNotMakeSplitPointActualValue.

setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.trees.LMT

Sets the value of doNotMakeSplitPointActualValue.

setDoNotOperateOnPerClassBasis(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Set the DoNotOperateOnPerClassBasis value.

setDoNotPrintModels(boolean) - Method in class weka.classifiers.meta.Vote

Set whether to print the individual ensemble models in the output

setDontCalculateOutOfBagError(boolean) - Method in class weka.classifiers.trees.RandomForest

Set whether to turn off the calculation of out of bag error

setDontFilterAfterFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.

setDontNormalize(boolean) - Method in class weka.classifiers.functions.SGD

Turn normalization off/on.

setDontNormalize(boolean) - Method in class weka.core.NormalizableDistance

Sets whether if the attribute values are to be normalized in distance calculation.

setDontReplaceMissing(boolean) - Method in class weka.classifiers.functions.SGD

Turn global replacement of missing values off/on.

setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.Canopy

Sets whether missing values are to be replaced.

setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.SimpleKMeans

Sets whether missing values are to be replaced.

setDontShowDialog(String) - Static method in class weka.core.Utils

Specify that the named dialog is not to be displayed in the future.

setDontShowDialogResponse(String, String) - Static method in class weka.core.Utils

Specify that the named dialog is not to be shown again in the future.

setEditable(boolean) - Method in class weka.gui.beans.EnvironmentField

Set the editable status of the combo box.

setEditedStatus(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setEditedStatus(int, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setElement(int, int, double) - Method in class weka.classifiers.CostMatrix

Set the value of a cell as a double

setElement(int, double) - Method in class weka.core.AlgVector

Sets an element of the matrix to the given value.

setElement(int, int, double) - Method in class weka.core.Matrix

Deprecated. Sets an element of the matrix to the given value.

setElementAt(E, int) - Method in class weka.core.FastVector

Deprecated. Sets the element at the given index.

setElementAt(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Sets the component at the specified index of this list to be the specified object.

setElements(double[]) - Method in class weka.core.AlgVector

Sets the elements of the vector to values of the given array.

setEliminateColinearAttributes(boolean) - Method in class weka.classifiers.functions.LinearRegression

Set the value of EliminateColinearAttributes.

setEnabled(boolean) - Method in class weka.core.Debug

sets whether the logging is enabled or not

setEnabled(boolean) - Method in class weka.core.Memory

sets whether the memory management is enabled

setEnabled(boolean) - Method in class weka.gui.beans.EnvironmentField

Set the enabled status of the combo box.

setEnabled(boolean) - Method in class weka.gui.beans.FileEnvironmentField

Set the enabled status of the combo box and button

setEnabled(boolean) - Method in class weka.gui.GenericObjectEditor

Sets whether the editor is "enabled", meaning that the current values will be painted.

setEnabled(boolean) - Method in class weka.gui.PropertyPanel

Passes on enabled/disabled status to the custom panel (if one is set).

setEnclosureCharacters(String) - Method in class weka.core.converters.CSVLoader

Set the character(s) to use/recognize as string enclosures

setEndTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Sets the value of the endTime property.

setEndTimeVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the endTimeVariable property.

setEntropicAutoBlend(boolean) - Method in class weka.classifiers.lazy.KStar

Set whether entropic blending is to be used.

setEnumerateColNames(boolean) - Method in class weka.experiment.ResultMatrix

sets whether the column names are prefixed with "(x)" where "x" is the index.

setEnumerateRowNames(boolean) - Method in class weka.experiment.ResultMatrix

sets whether to the row names are prefixed with the index.

setEnvironment(Environment) - Method in class weka.classifiers.meta.Vote

Set environment variable values to substitute in the paths of serialized models to load

setEnvironment(Environment) - Method in class weka.classifiers.misc.InputMappedClassifier

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.core.converters.AbstractFileLoader

Set the environment variables to use.

setEnvironment(Environment) - Method in class weka.core.converters.AbstractFileSaver

Set the environment variables to use.

setEnvironment(Environment) - Method in class weka.core.converters.DatabaseLoader

Set the environment variables to use.

setEnvironment(Environment) - Method in class weka.core.converters.DatabaseSaver

Set the environment variables to use.

setEnvironment(Environment) - Method in interface weka.core.EnvironmentHandler

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.AddUserFields

Set environment varialbes to use

setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

setEnvironment(Environment) - Method in class weka.gui.beans.Associator

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.AttributeSummarizerCustomizer

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.Classifier

Set environment variables to pass on to the classifier (if if is an EnvironmentHandler)

setEnvironment(Environment) - Method in class weka.gui.beans.ClassifierCustomizer

Set any environment variables to pass to the PropertySheetPanel

setEnvironment(Environment) - Method in class weka.gui.beans.DataVisualizer

setEnvironment(Environment) - Method in class weka.gui.beans.DataVisualizerCustomizer

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.EnvironmentField

Set the environment variables to display in the drop down list.

setEnvironment(Environment) - Method in class weka.gui.beans.FlowByExpression

setEnvironment(Environment) - Method in class weka.gui.beans.FlowByExpressionCustomizer

setEnvironment(Environment) - Method in class weka.gui.beans.FlowRunner

Set the environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.ImageSaver

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.ImageSaverCustomizer

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.Join

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.JoinCustomizer

setEnvironment(Environment) - Method in class weka.gui.beans.KnowledgeFlowApp

Set the environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.Loader

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.LoaderCustomizer

setEnvironment(Environment) - Method in class weka.gui.beans.ModelPerformanceChart

setEnvironment(Environment) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.Saver

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.SaverCustomizer

setEnvironment(Environment) - Method in class weka.gui.beans.SerializedModelSaver

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.SerializedModelSaverCustomizer

setEnvironment(Environment) - Method in class weka.gui.beans.Sorter

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SorterCustomizer

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabeler

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabelerCustomizer

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabelerRules

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacer

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacerCustomizer

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacerRules

setEnvironment(Environment) - Method in class weka.gui.beans.TextSaver

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.beans.TextSaverCustomizer

Set the environment variables to use

setEnvironment(Environment) - Method in class weka.gui.filters.AddUserFieldsCustomizer

Set environment variables to use

setEnvironment(Environment) - Method in class weka.gui.PropertySheetPanel

Set environment variables to pass on to any editor that can use them

setEpochs(int) - Method in class weka.classifiers.functions.SGD

Set the number of epochs to use

setEpochs(int) - Method in class weka.classifiers.functions.SGDText

Set the number of epochs to use

setEpsilon(double) - Method in class weka.classifiers.functions.SGD

Set the epsilon threshold on the error for epsilon insensitive and Huber loss functions

setEpsilon(double) - Method in class weka.classifiers.functions.SMO

Set the value of epsilon.

setEpsilon(double) - Method in class weka.classifiers.functions.supportVector.RegSMO

Set the value of epsilon.

setEpsilonParameter(double) - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Set the value of epsilon parameter of the epsilon insensitive loss function.

setErrorOnProbabilities(boolean) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of errorOnProbabilities.

setErrorOnProbabilities(boolean) - Method in class weka.classifiers.trees.LMT

Set the value of errorOnProbabilities.

setErrorPlotPointSizeProportionalToMargin(boolean) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Set whether the point size on classification error plots should be proportional to the prediction margin.

setEstimator(BayesNetEstimator) - Method in class weka.classifiers.bayes.BayesNet

Set the Estimator Algorithm used in calculating the CPTs

setEstimator(Estimator) - Method in class weka.estimators.CheckEstimator

Set the estimator for boosting.

setEstimatorType(SelectedTag) - Method in class weka.classifiers.meta.RegressionByDiscretization

Set the estimator

setEuclidean(Euclidean) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the euclidean property.

setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Sets the distance function used to (or to be used to) build the tree.

setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets the distance function to use to build the tree.

setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Sets the EuclideanDistance object to use for splitting nodes.

setEvaluation(Evaluation) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper

Sets the Evaluation object to use

setEvaluation(Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Sets the Evaluation object to use.

setEvaluationMeasure(SelectedTag) - Method in class weka.attributeSelection.WrapperSubsetEval

Sets the performance evaluation measure to use for selecting attributes for the decision table

setEvaluationMeasure(SelectedTag) - Method in class weka.classifiers.rules.DecisionTable

Sets the performance evaluation measure to use for selecting attributes for the decision table

setEvaluationMetric(SelectedTag) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Set the evaluation metric to use

setEvaluationMetricsToOutput(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Set the evaluation metrics to output (as a comma-separated list).

setEvaluator(ASEvaluation) - Method in class weka.attributeSelection.AttributeSelection

set the attribute/subset evaluator

setEvaluator(ASEvaluation) - Method in class weka.attributeSelection.CheckAttributeSelection

Set the evaluator to test.

setEvaluator(ASEvaluation) - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Sets the attribute evaluator

setEvaluator(ASEvaluation) - Method in class weka.filters.supervised.attribute.AttributeSelection

set attribute/subset evaluator

setEvalUsingTrainingData(boolean) - Method in class weka.attributeSelection.OneRAttributeEval

Use the training data to evaluate attributes rather than cross validation

setEvidence(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

set evidence state of a node.

setEvidence(int, int) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

setEvidence(int, int) - Method in class weka.classifiers.bayes.net.MarginCalculator

setExecuting(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setExecuting(int, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setExecutionSlots(int) - Method in class weka.gui.beans.Classifier

Set the number of execution slots (threads) to use to train models with.

setExecutionSlots(int) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Set the number of executions slots to use.

setExecutionStatus(int) - Method in class weka.experiment.TaskStatusInfo

Set the execution status of this Task.

setExecutionThread(KnowledgeFlowApp.RunThread) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setExecutionThread(int, KnowledgeFlowApp.RunThread) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setExitIfNoWindowsOpen(boolean) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Sets whether System.exit gets called when no more windows are open.

setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewer

whether to do a System.exit(0) on close

setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

whether to do a System.exit(0) on close

setExpectedResultsPerAverage(int) - Method in class weka.experiment.AveragingResultProducer

Set the value of ExpectedResultsPerAverage.

setExperiment(Experiment) - Method in class weka.experiment.RemoteExperimentSubTask

Set the experiment for this sub task

setExperiment(Experiment) - Method in class weka.gui.experiment.AlgorithmListPanel

Tells the panel to act on a new experiment.

setExperiment(Experiment) - Method in class weka.gui.experiment.DatasetListPanel

Tells the panel to act on a new experiment.

setExperiment(Experiment) - Method in class weka.gui.experiment.DistributeExperimentPanel

Sets the experiment to be configured.

setExperiment(Experiment) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel

Sets the experiment which will have the custom properties edited.

setExperiment(RemoteExperiment) - Method in class weka.gui.experiment.HostListPanel

Tells the panel to act on a new experiment.

setExperiment(Experiment) - Method in class weka.gui.experiment.ResultsPanel

Tells the panel to use a new experiment.

setExperiment(Experiment) - Method in class weka.gui.experiment.RunNumberPanel

Sets the experiment to be configured.

setExperiment(Experiment) - Method in class weka.gui.experiment.RunPanel

Sets the experiment the panel operates on.

setExperiment(Experiment) - Method in class weka.gui.experiment.SetupPanel

Sets the experiment to configure.

setExperiment(Experiment) - Method in class weka.gui.experiment.SimpleSetupPanel

Sets the experiment to configure.

setExplicitPropsFile(boolean) - Method in class weka.gui.GenericPropertiesCreator

if FALSE, the locating of a props-file of the Utils-class is used, otherwise it's tried to load the specified file

setExplorer(Explorer) - Method in class weka.gui.explorer.AssociationsPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorer(Explorer) - Method in class weka.gui.explorer.AttributeSelectionPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorer(Explorer) - Method in class weka.gui.explorer.ClassifierPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data).

setExplorer(Explorer) - Method in class weka.gui.explorer.ClustererPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorer(Explorer) - Method in interface weka.gui.explorer.Explorer.ExplorerPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorer(Explorer) - Method in class weka.gui.explorer.PreprocessPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorer(Explorer) - Method in class weka.gui.explorer.VisualizePanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExponent(double) - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel

Sets the exponent value (must be different from 1.0).

setExponent(double) - Method in class weka.classifiers.functions.supportVector.PolyKernel

Sets the exponent value.

setExponent(double) - Method in class weka.classifiers.functions.VotedPerceptron

Set the value of exponent.

setExponent(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the exponent property.

setExponent(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Sets the value of the exponent property.

setExpression(String) - Method in class weka.datagenerators.classifiers.regression.Expression

Sets the mathematical expression to generate y out of x.

setExpression(String) - Method in class weka.filters.unsupervised.attribute.AddExpression

Set the expression to apply

setExpression(String) - Method in class weka.filters.unsupervised.attribute.MathExpression

Set the expression to apply

setExpression(String) - Method in class weka.filters.unsupervised.attribute.RemoveByName

Sets the regular expression to match the attribute names against.

setExpression(String) - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Sets the expression used for filtering.

setExpressionString(String) - Method in class weka.gui.beans.FlowByExpression

Set the expression (in internal format)

setExtender(String) - Method in class weka.core.pmml.jaxbbindings.Extension

Sets the value of the extender property.

setExtremeValuesAsOutliers(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Set whether extreme values are also tagged as outliers.

setExtremeValuesFactor(double) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Sets the factor for determining the thresholds for extreme values.

setFalse(False) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the false property.

setFalse(False) - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Sets the value of the false property.

setFalse(False) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the false property.

setFalse(False) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the false property.

setFalseNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats

Sets the number of positive instances predicted as negative

setFalsePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats

Sets the number of negative instances predicted as positive

setFalseStepName(String) - Method in class weka.gui.beans.FlowByExpression

Set the name of the connected step to send "false" instances to

setFastDistanceCalc(boolean) - Method in class weka.clusterers.SimpleKMeans

Sets whether to use faster distance calculation.

setFastRegression(boolean) - Method in class weka.classifiers.trees.LMT

Set the value of fastRegression.

setFeature(RESULTFEATURE) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the feature property.

setFeature(RESULTFEATURE) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the feature property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.Discretize

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldRef

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldValue

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.InstanceField

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.KNNInput

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the field property.

setField(String) - Method in class weka.core.pmml.jaxbbindings.VerificationField

Sets the value of the field property.

setFieldCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Sets the value of the fieldCount property.

setFieldCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the fieldCount property.

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.DerivedFieldMetaInfo

Upadate the field definitions for this derived field

setFieldDefs(Instances) - Method in class weka.core.pmml.DerivedFieldMetaInfo

Upadate the field definitions for this derived field

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Discretize

Set the field definitions for this Expression to use

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Expression

Set the field definitions for this Expression to use

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.FieldRef

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.NormContinuous

Set the field definitions for this Expression to use

setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.NormDiscrete

Set the field definitions for this Expression to use

setFieldName(String) - Method in class weka.core.pmml.jaxbbindings.BayesInput

Sets the value of the fieldName property.

setFieldName(String) - Method in class weka.core.pmml.jaxbbindings.BayesOutput

Sets the value of the fieldName property.

setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the fieldRef property.

setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the fieldRef property.

setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the fieldRef property.

setFieldSeparator(String) - Method in class weka.core.converters.CSVLoader

Sets the character used as column separator.

setFieldSeparator(String) - Method in class weka.core.converters.CSVSaver

Sets the character used as column separator.

setFieldWeight(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the fieldWeight property.

setFieldWeight(Double) - Method in class weka.core.pmml.jaxbbindings.KNNInput

Sets the value of the fieldWeight property.

setFile(File) - Method in class weka.core.converters.AbstractFileLoader

sets the source File

setFile(File) - Method in class weka.core.converters.AbstractFileSaver

Sets the destination file.

setFile(File) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setFile(File) - Method in class weka.core.converters.ArffLoader

sets the source File

setFile(File) - Method in class weka.core.converters.ArffSaver

Sets the destination file.

setFile(File) - Method in interface weka.core.converters.FileSourcedConverter

Set the file to load from/ to save in

setFile(File) - Method in class weka.core.converters.JSONSaver

Sets the destination file.

setFile(File) - Method in interface weka.core.converters.Saver

Sets the output file

setFile(File) - Method in class weka.core.converters.XRFFSaver

Sets the destination file.

setFile(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument

Sets the value of the file property.

setFile(File) - Method in class weka.gui.visualize.JComponentWriter

sets the file to store the output in

setFileFormat(Tag) - Method in class weka.gui.beans.SerializedModelSaver

Set the file format to use for saving.

setFileMustExist(boolean) - Method in class weka.gui.ConverterFileChooser

Whether the selected file must exst (only open dialog).

setFilename(String) - Method in class weka.core.FindWithCapabilities

Sets the dataset filename to base the capabilities on.

setFilename(String) - Method in class weka.gui.arffviewer.ArffPanel

sets the filename

setFilename(int, String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

sets the filename of the specified panel

setFilename(String) - Method in class weka.gui.beans.ImageSaver

Set the filename to save to

setFilename(String) - Method in class weka.gui.beans.TextSaver

Set the filename to save to

setFilePrefix(String) - Method in class weka.core.converters.AbstractFileSaver

Sets the file name prefix

setFilePrefix(String) - Method in class weka.core.converters.AbstractSaver

Default implementation throws an IOException.

setFilePrefix(String) - Method in interface weka.core.converters.Saver

Sets the file prefix.

setFillWithMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Sets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).

setFilter(Filter) - Method in class weka.associations.FilteredAssociator

Sets the filter

setFilter(Filter) - Method in class weka.classifiers.meta.FilteredClassifier

Sets the filter

setFilter(Filter) - Method in class weka.clusterers.FilteredClusterer

Sets the filter.

setFilter(Filter) - Method in class weka.filters.CheckSource

Sets the filter to use for the comparison.

setFilter(Filter) - Method in class weka.gui.beans.Filter

Set the filter to be wrapped by this bean

setFilterAfterFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.

setFilters(Filter[]) - Method in class weka.filters.MultiFilter

Sets the list of possible filters to choose from.

setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Sets the list of possible filters to choose from.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcesses

Sets how the training data will be transformed.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMO

Sets how the training data will be transformed.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMOreg

Sets how the training data will be transformed.

setFind(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Sets the regular expression that the attribute names must match.

setFindAllRulesForSupportLevel(boolean) - Method in class weka.associations.FPGrowth

If true then turn off the iterative support reduction method of finding x rules that meet the minimum support and metric thresholds and just return all the rules that meet the lower bound on minimum support and the minimum metric.

setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize

Set the value of FindNumBins.

setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Set the value of FindNumBins.

setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Sets index of the first value used.

setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues

Sets index of the first value used.

setFlow(Vector<Vector<?>>) - Method in class weka.gui.beans.KnowledgeFlowApp

Set the flow for the KnowledgeFlow to edit.

setFlowFile(File) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setFlowFile(int, File) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setFlows(Vector<Object>) - Method in class weka.gui.beans.FlowRunner

Set the vector holding the flows(s) to run

setFocus() - Method in class weka.gui.sql.ConnectionPanel

sets the focus in a designated control.

setFocus() - Method in class weka.gui.sql.InfoPanel

sets the focus in a designated control

setFocus() - Method in class weka.gui.sql.QueryPanel

sets the focus in a designated control.

setFocus() - Method in class weka.gui.sql.ResultPanel

sets the focus in a designated control

setFold(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Selects a fold.

setFold(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Selects a fold.

setFoldColumn(int) - Method in class weka.experiment.PairedTTester

Set the value of FoldColumn.

setFoldColumn(int) - Method in interface weka.experiment.Tester

Set the value of FoldColumn.

setFolds(int) - Method in class weka.attributeSelection.AttributeSelection

set the number of folds for cross validation

setFolds(int) - Method in class weka.attributeSelection.OneRAttributeEval

Set the number of folds to use for cross validation

setFolds(int) - Method in class weka.attributeSelection.WrapperSubsetEval

Set the number of folds to use for accuracy estimation

setFolds(int) - Method in class weka.classifiers.rules.JRip

Sets the number of folds to use

setFolds(int) - Method in class weka.gui.beans.CrossValidationFoldMaker

Set the number of folds for the cross validation

setFont(Font) - Method in class weka.gui.visualize.PostscriptGraphics

Set current font.

setFontName(String) - Method in class weka.gui.scripting.SyntaxDocument

sets the current font family (affects all built-in styles).

setFontSize(int) - Method in class weka.gui.scripting.SyntaxDocument

sets the current font size (affects all built-in styles).

setFontSizeAdjust(int) - Method in class weka.gui.beans.Note

set the font size adjustment

setFormat(String) - Method in class weka.core.Debug.Timestamp

sets the format for the timestamp

setFrom(String) - Method in class weka.core.pmml.jaxbbindings.Con1

Sets the value of the from property.

setFStatistic(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the fStatistic property.

setFStatistic(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the fStatistic property.

setFunction(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate

Sets the value of the function property.

setFunction(String) - Method in class weka.core.pmml.jaxbbindings.Apply

Sets the value of the function property.

setFunction(SelectedTag) - Method in class weka.datagenerators.classifiers.classification.Agrawal

Sets the function for generating the data.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.MiningModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Sets the value of the functionName property.

setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the functionName property.

setFValue(Double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the fValue property.

setGamma(double) - Method in class weka.classifiers.functions.supportVector.RBFKernel

Sets the gamma value.

setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType

Sets the value of the gamma property.

setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType

Sets the value of the gamma property.

setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType

Sets the value of the gamma property.

setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Sets the value of the gamma property.

setGap(GAP) - Method in class weka.core.pmml.jaxbbindings.Delimiter

Sets the value of the gap property.

setGaussianDistribution(GaussianDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate

Sets the value of the gaussianDistribution property.

setGaussianDistribution(GaussianDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the gaussianDistribution property.

setGeneralRegressionModel(GeneralRegressionModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the generalRegressionModel property.

setGenerateRanking(boolean) - Method in class weka.attributeSelection.GreedyStepwise

Records whether the user has requested a ranked list of attributes.

setGenerateRanking(boolean) - Method in interface weka.attributeSelection.RankedOutputSearch

Sets whether or not ranking is to be performed.

setGenerateRanking(boolean) - Method in class weka.attributeSelection.Ranker

This is a dummy set method---Ranker is ONLY capable of producing a ranked list of attributes for attribute evaluators.

setGenerator(DataGenerator) - Method in class weka.gui.explorer.DataGeneratorPanel

sets the generator to use initially

setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the base for computing the number of samples to obtain from each generator.

setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the base for computing the number of samples to obtain from each generator.

setGlobalBlend(int) - Method in class weka.classifiers.lazy.KStar

Set the global blend parameter

setGlobalModel(NBTreeNoSplit) - Method in class weka.classifiers.trees.j48.NBTreeSplit

Set the global naive bayes model for this node

setGlobalTermWeights(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Sets the value of the globalTermWeights property.

setGracePeriod(double) - Method in class weka.classifiers.trees.HoeffdingTree

Set the number of instances (or total weight of instances) a leaf should observe between split attempts

setGridWidth(int) - Method in class weka.gui.beans.AttributeSummarizer

Set the width of the grid of plots

setGroupField(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate

Sets the value of the groupField property.

setGroupIdentifier(long) - Method in class weka.gui.beans.BatchClassifierEvent

setGUI(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

This will set whether A GUI is brought up to allow interaction by the user with the neural network during training.

setGUIType(SelectedTag) - Method in class weka.gui.Main

Sets the type of GUI to use.

setHandler(CapabilitiesHandler) - Method in class weka.core.FindWithCapabilities

sets the Capabilities handler to generate the data for.

setHandler(CapabilitiesHandler) - Method in class weka.core.TestInstances

sets the Capabilities handler to generate the data for

setHandleRightClicks(boolean) - Method in class weka.gui.ResultHistoryPanel

Set whether the result history list should handle right clicks or whether the parent object will handle them.

setHeader(Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the header of the dataset.

setHeader(Header) - Method in class weka.core.pmml.jaxbbindings.PMML

Sets the value of the header property.

setHeuristicStop(int) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of heuristicStop.

setHeuristicStop(int) - Method in class weka.classifiers.trees.lmt.LogisticBase

Sets the option "heuristicStop".

setHidden(boolean) - Method in class weka.gui.beans.BeanConnection

Make this connection invisible on the display

setHiddenLayers(String) - Method in class weka.classifiers.functions.MultilayerPerceptron

This will set what the hidden layers are made up of when auto build is enabled.

setHighlight(String) - Method in class weka.gui.treevisualizer.TreeVisualizer

Set the highlight for the node with the given id

setHighlighted(boolean) - Method in class weka.gui.beans.Note

setHighValue(Double) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the highValue property.

setHistory(DefaultListModel) - Method in class weka.gui.sql.ConnectionPanel

sets the local history to the given one.

setHistory(DefaultListModel) - Method in class weka.gui.sql.QueryPanel

sets the local history to the given one.

setHoeffdingTieThreshold(double) - Method in class weka.classifiers.trees.HoeffdingTree

Set the threshold below which a split will be forced to break ties

setId(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Item

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Itemset

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.NeuralInput

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Neuron

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Node

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument

Sets the value of the id property.

setId(String) - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Sets the value of the id property.

setID(int) - Method in class weka.core.Tag

Sets the numeric ID of the Tag.

setIDFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.

setIDIndex(String) - Method in class weka.filters.unsupervised.attribute.AddID

Sets index of the attribute used.

setIDStr(String) - Method in class weka.core.Tag

Sets the string ID of the Tag.

setIgnoreCase(boolean) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

setIgnoreCase(boolean) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Set whether to ignore case when matching

setIgnoreCase(boolean) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Set whether to ignore case when matching

setIgnoreCaseForNames(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier

Set whether to ignore case when matching attribute names and nominal values.

setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Set the IgnoreClass value.

setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AddCluster

Sets the ranges of attributes to be ignored.

setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Sets the ranges of attributes to be ignored.

setIgnoredProperties(String) - Method in class weka.core.CheckGOE

Sets the properties to ignore in checkToolTips().

setIgnoreRange(String) - Method in class weka.filters.unsupervised.attribute.MathExpression

Set which attributes are to be ignored

setImportance(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the importance property.

setImportance(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the importance property.

setIncludeClass(boolean) - Method in class weka.core.InstanceComparator

Sets whether the class should be included in the comparison.

setIncludeClass(boolean) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Sets whether the class can be cleaned, too.

setIncludeRelationName(boolean) - Method in class weka.gui.beans.SerializedModelSaver

Set whether the relation name of the training data used to create the model should be included as part of the filename for the serialized model.

setIndentationSize(int) - Method in class weka.gui.scripting.SyntaxDocument

Sets the number of blanks to use for indentation.

setIndex(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeValue

Sets the value of the index property.

setIndex(int) - Method in class weka.core.pmml.MiningFieldMetaInfo

Set the index of this field in the mining schema Instances

setInfoData(Vector<Instances>) - Method in interface weka.gui.visualize.InstanceInfo

Sets the underlying data.

setInfoData(Vector<Instances>) - Method in class weka.gui.visualize.InstanceInfoFrame

Sets the underlying data.

setInfoText(String) - Method in interface weka.gui.visualize.InstanceInfo

Sets the text to display.

setInfoText(String) - Method in class weka.gui.visualize.InstanceInfoFrame

Sets the text to display.

setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Sets whether to init as naive bayes

setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2

Sets whether to init as naive bayes

setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Sets whether to init as naive bayes

setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2

Sets whether to init as naive bayes

setInitFile(File) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Sets the file to initialize the filter with, can be null.

setInitFileClassIndex(String) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Sets class index of the file to initialize the filter with.

setInitialAnchorRandom(boolean) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets whether if the initial anchor is chosen randomly.

setInitialCount(double) - Method in class weka.classifiers.trees.REPTree

Set the value of InitialCount.

setInitializationMethod(SelectedTag) - Method in class weka.clusterers.SimpleKMeans

Set the initialization method to use

setInitialScore(Double) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the initialScore property.

setInitialSplitPaneDividerLocation() - Method in class weka.gui.PackageManager

Setting the initial placement of the divider line on a JSplitPane is problematic.

setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the inlineTable property.

setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the inlineTable property.

setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Sets the value of the inlineTable property.

setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the inlineTable property.

setInputFilename(String) - Method in class weka.gui.GenericPropertiesCreator

sets the file to get the information about the packages from.

setInputFormat(Instances) - Method in class weka.filters.AllFilter

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.Filter

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.SimpleFilter

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.ClassOrder

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.Discretize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.NominalToBinary

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.PartitionMembership

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.instance.Resample

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.instance.SpreadSubsample

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Add

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddCluster

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddExpression

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddID

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddNoise

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddUserFields

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Center

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Copy

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FirstOrder

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MathExpression

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToString

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Normalize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericToBinary

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Obfuscate

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Remove

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveType

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Reorder

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Standardize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToNominal

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SwapValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Randomize

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemovePercentage

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveRange

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Resample

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.ReservoirSample

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse

Sets the format of the input instances.

setInputOrder(SelectedTag) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the input order.

setInputs(Vector<Object>) - Method in class weka.gui.beans.MetaBean

setInsertDummyNominalFirstValue(boolean) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Set whether to insert a dummy first value in the definition for each nominal attribute or not.

setInstance(Instance) - Method in class weka.gui.beans.InstanceEvent

Set the instance

setInstanceFields(InstanceFields) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the instanceFields property.

setInstanceIdVariable(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the instanceIdVariable property.

setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Sets the master index array containing indices of the training instances.

setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.

setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.

setInstanceList(int[]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Sets the master index array containing indices of the training instances.

setInstanceRange(int) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Sets the number of instances forward to translate values between.

setInstances(Instances) - Method in class weka.core.converters.AbstractSaver

Sets instances that should be stored.

setInstances(Instances) - Method in class weka.core.converters.JSONSaver

Sets instances that should be stored.

setInstances(Instances) - Method in class weka.core.converters.LibSVMSaver

Sets instances that should be stored.

setInstances(Instances) - Method in interface weka.core.converters.Saver

Sets the instances to be saved

setInstances(Instances) - Method in class weka.core.converters.SVMLightSaver

Sets instances that should be stored.

setInstances(Instances) - Method in class weka.core.converters.XRFFSaver

Sets instances that should be stored.

setInstances(Instances) - Method in interface weka.core.DistanceFunction

Sets the instances.

setInstances(Instances) - Method in class weka.core.neighboursearch.BallTree

Builds the BallTree based on the given set of instances.

setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Sets the training instances on which the tree is (or is to be) built.

setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets the instances on which the tree is to be built.

setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the instances on which the tree is to be built.

setInstances(Instances) - Method in class weka.core.neighboursearch.CoverTree

Builds the Cover Tree on the given set of instances.

setInstances(Instances) - Method in class weka.core.neighboursearch.KDTree

Builds the KDTree on the given set of instances.

setInstances(Instances) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Sets the training instances on which the tree is (or is to be) built.

setInstances(Instances) - Method in class weka.core.neighboursearch.LinearNNSearch

Sets the instances comprising the current neighbourhood.

setInstances(Instances) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Sets the instances.

setInstances(Instances) - Method in class weka.core.NormalizableDistance

Sets the instances.

setInstances(Instances) - Method in class weka.core.xml.XMLInstances

builds up the XML structure based on the given data

setInstances(Instances) - Method in class weka.experiment.AveragingResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in class weka.experiment.CrossValidationResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in class weka.experiment.DatabaseResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in class weka.experiment.LearningRateResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in class weka.experiment.PairedTTester

Set the value of Instances.

setInstances(Instances) - Method in class weka.experiment.RandomSplitResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in interface weka.experiment.ResultProducer

Sets the dataset that results will be obtained for.

setInstances(Instances) - Method in interface weka.experiment.Tester

Set the value of Instances.

setInstances(Instances) - Method in class weka.gui.arffviewer.ArffPanel

displays the given instances, i.e.

setInstances(Instances) - Method in class weka.gui.arffviewer.ArffSortedTableModel

sets the data

setInstances(Instances) - Method in class weka.gui.arffviewer.ArffTableModel

sets the data

setInstances(Instances) - Method in class weka.gui.AttributeListPanel

Sets the instances who's attribute names will be displayed.

setInstances(Instances) - Method in class weka.gui.AttributeSelectionPanel

Sets the instances who's attribute names will be displayed.

setInstances(Instances) - Method in class weka.gui.AttributeSummaryPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.AttributeVisualizationPanel

Sets the instances for use

setInstances(Instances) - Method in class weka.gui.beans.AttributeSummarizer

Set instances for this bean.

setInstances(Instances) - Method in class weka.gui.beans.DataVisualizer

Set instances for this bean.

setInstances(Instances) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Set instances (if the perspective accepts them)

setInstances(Instances) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setInstances(Instances) - Method in class weka.gui.beans.ScatterPlotMatrix

Set instances for this bean.

setInstances(Instances) - Method in class weka.gui.beans.SQLViewerPerspective

Set instances (if the perspective accepts them)

setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Set the training instances

setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the training data

setInstances(Instances) - Method in class weka.gui.experiment.ResultsPanel

Sets up the panel with a new set of instances, attempting to guess the correct settings for various columns.

setInstances(Instances) - Method in class weka.gui.explorer.AbstractPlotInstances

Sets the instances that are the basis for the plot instances.

setInstances(Instances) - Method in class weka.gui.explorer.AssociationsPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.explorer.AttributeSelectionPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.explorer.ClassifierPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.explorer.ClustererPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in interface weka.gui.explorer.Explorer.ExplorerPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.explorer.PreprocessPanel

Tells the panel to use a new base set of instances.

setInstances(Instances) - Method in class weka.gui.InstancesSummaryPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.SetInstancesPanel

Updates the set of instances that is currently held by the panel.

setInstances(Instances) - Method in class weka.gui.ViewerDialog

sets the instances to display

setInstances(Instances) - Method in class weka.gui.visualize.AttributePanel

This sets the instances to be drawn into the attribute panel

setInstances(Instances) - Method in class weka.gui.visualize.ClassPanel

Set the instances.

setInstances(Instances) - Method in class weka.gui.visualize.MatrixPanel

This method changes the Instances object of this class to a new one.

setInstances(Instances) - Method in class weka.gui.visualize.Plot2D

Sets the master plot from a set of instances

setInstances(Instances) - Method in class weka.gui.visualize.VisualizePanel

Tells the panel to use a new set of instances.

setInstancesFromDB(InstanceQuery) - Method in class weka.gui.explorer.PreprocessPanel

Loads instances from a database

setInstancesFromDBQ(String, String, String, String) - Method in class weka.gui.explorer.PreprocessPanel

Loads (non-sparse) instances from an SQL query the user provided with the SqlViewerDialog, then loads the instances in a background process.

setInstancesFromDBQ(String, String, String, String, boolean) - Method in class weka.gui.explorer.PreprocessPanel

Loads instances from an SQL query the user provided with the SqlViewerDialog, then loads the instances in a background process.

setInstancesFromFile(AbstractFileLoader) - Method in class weka.gui.explorer.PreprocessPanel

Loads results from a set of instances retrieved with the supplied loader.

setInstancesFromFileQ() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Queries the user for a file to load instances from, then loads the instances in a background process.

setInstancesFromFileQ() - Method in class weka.gui.explorer.PreprocessPanel

Queries the user for a file to load instances from, then loads the instances in a background process.

setInstancesFromFileQ() - Method in class weka.gui.SetInstancesPanel

Queries the user for a file to load instances from, then loads the instances in a background process.

setInstancesFromURL(URL) - Method in class weka.gui.explorer.PreprocessPanel

Loads instances from a URL.

setInstancesFromURLQ() - Method in class weka.gui.explorer.PreprocessPanel

Queries the user for a URL to load instances from, then loads the instances in a background process.

setInstancesFromURLQ() - Method in class weka.gui.SetInstancesPanel

Queries the user for a URL to load instances from, then loads the instances in a background process.

setInstancesIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveRange

Sets the ranges of instances to be selected.

SetInstancesPanel - Class in weka.gui

A panel that displays an instance summary for a set of instances and lets the user open a set of instances from either a file or URL.

SetInstancesPanel() - Constructor for class weka.gui.SetInstancesPanel

Default constructor.

SetInstancesPanel(boolean, boolean, ConverterFileChooser) - Constructor for class weka.gui.SetInstancesPanel

Create the panel.

setInterAnchorDistances(Vector<MiddleOutConstructor.TempNode>, MiddleOutConstructor.TempNode, Vector<double[]>) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the distances of a supplied new anchor to all the rest of the previous anchor points.

setIntercept(double) - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Sets the value of the intercept property.

setInternalCacheSize(int) - Method in class weka.classifiers.functions.supportVector.StringKernel

sets the size of the internal cache for intermediate results.

setInterpolationMethod(INTERPOLATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Sets the value of the interpolationMethod property.

setInterQuartileRange(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the interQuartileRange property.

setInterval(Interval) - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin

Sets the value of the interval property.

setInvalidFreq(Double) - Method in class weka.core.pmml.jaxbbindings.Counts

Sets the value of the invalidFreq property.

setInvalidValueTreatment(INVALIDVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.Apply

Sets the value of the invalidValueTreatment property.

setInvalidValueTreatment(INVALIDVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the invalidValueTreatment property.

setInvert(boolean) - Method in class weka.core.InstanceComparator

Sets whether to invert the matching sense of the attribute range.

setInvert(boolean) - Method in class weka.core.Range

Sets whether the range sense is inverted, i.e.

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Set whether selection is inverted.

setInvertSelection(boolean) - Method in interface weka.core.DistanceFunction

Sets whether the matching sense of attribute indices is inverted or not.

setInvertSelection(boolean) - Method in class weka.core.NormalizableDistance

Sets whether the matching sense of attribute indices is inverted or not.

setInvertSelection(boolean) - Method in class weka.filters.supervised.attribute.Discretize

Sets whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Set whether selected attributes should be acted on or all other attributes.

setInvertSelection(boolean) - Method in class weka.filters.supervised.instance.Resample

Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).

setInvertSelection(boolean) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Sets if selection is to be inverted.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Copy

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.MathExpression

Set whether selected columns should be select or unselect.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Set whether selected attributes should be acted on or all other attributes.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Sets whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Sets whether the selection of the indices is inverted or not

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Sets whether selected columns should be worked on or all the others apart from these.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Set whether selected columns should be transformed or not.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Remove

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RemoveByName

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RemoveType

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Sets whether to invert the selection of the attributes.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Set whether selected columns should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.SortLabels

Sets whether selected columns should be processed or skipped.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether selected columns should be processed or skipped.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Sets if selection is to be inverted.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Set whether selected values should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemovePercentage

Sets if selection is to be inverted.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveRange

Sets if selection is to be inverted.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Set whether selected values should be removed or kept.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.Resample

Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).

setIRClassValue(String) - Method in class weka.attributeSelection.WrapperSubsetEval

Set the class value (label or index) to use with IR metric evaluation of subsets.

setIsCenterField(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the isCenterField property.

setIsCyclic(String) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the isCyclic property.

setIsIntercept(Boolean) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the isIntercept property.

setIsMultiValued(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the isMultiValued property.

setIsRecursive(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the isRecursive property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.MiningModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Sets the value of the isScorable property.

setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the isScorable property.

setIsTransformed(Boolean) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the isTransformed property.

setItem(int[]) - Method in class weka.associations.ItemSet

Sets an item sets

setItemAt(int, int) - Method in class weka.associations.ItemSet

Sets the index of an attribute value

setItemRef(String) - Method in class weka.core.pmml.jaxbbindings.ItemRef

Sets the value of the itemRef property.

setIterativeClassifier(IterativeClassifier) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Set the base learner.

setJaccard(Jaccard) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the jaccard property.

setJitter(int) - Method in class weka.gui.visualize.Plot2D

Set level of jitter and repaint the plot using the new jitter value

setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcesses

Sets the kernel to use.

setKernel(Kernel) - Method in class weka.classifiers.functions.SMO.BinarySMO

sets the kernel to use

setKernel(Kernel) - Method in class weka.classifiers.functions.SMO

sets the kernel to use

setKernel(Kernel) - Method in class weka.classifiers.functions.SMOreg

sets the kernel to use

setKernel(Kernel) - Method in class weka.classifiers.functions.supportVector.CheckKernel

Set the lernel to test.

setKernel(Kernel) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Sets the kernel to use.

setKernelBandwidth(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Set the kernel bandwidth (number of nearest neighbours to cover)

setKernelFactorExpression(String) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Sets the expression for the kernel.

setKernelMatrixFile(File) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Sets the file holding the kernel matrix

setKeyFieldName(String) - Method in class weka.experiment.AveragingResultProducer

Set the value of KeyFieldName.

setKeys(String) - Method in class weka.core.converters.DatabaseLoader

Sets the key columns of a database table

setKeySpec(String) - Method in class weka.gui.beans.Join

Set the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)

setKeywords(String) - Method in class weka.experiment.DatabaseUtils

Sets the keywords (comma-separated list) to use.

setKeywordsMaskChar(String) - Method in class weka.experiment.DatabaseUtils

Sets the mask character to append to table or attribute names that are a reserved keyword.

setKind(String) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the kind property.

setKind(String) - Method in class weka.core.pmml.jaxbbindings.Matrix

Sets the value of the kind property.

setKNN(int) - Method in class weka.classifiers.lazy.IBk

Set the number of neighbours the learner is to use.

setKNN(int) - Method in class weka.classifiers.lazy.LWL

Sets the number of neighbours used for kernel bandwidth setting.

setKohonenMap(KohonenMap) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the kohonenMap property.

setKValue(int) - Method in class weka.classifiers.trees.RandomTree

Set the value of K.

setLabel(String) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Sets the value of the label property.

setLabel(String) - Method in class weka.core.pmml.jaxbbindings.Parameter

Sets the value of the label property.

setLabel(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Sets label of the merged class.

setLabel(String) - Method in class weka.gui.beans.BatchClassifierEvent

Set the label for this event.

setLabel(String) - Method in class weka.gui.beans.EnvironmentField

Set the label for this widget.

setLabel(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Set the label to assign if this rule matches, or empty string if binary flag attribute is being created.

setLabels(String) - Method in class weka.filters.unsupervised.attribute.AddValues

Sets the comma-separated list of labels.

setLambda(double) - Method in class weka.classifiers.functions.SGD

Set the value of lambda to use

setLambda(double) - Method in class weka.classifiers.functions.SGDText

Set the value of lambda to use

setLambda(double) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets the lambda constant used in the string kernel

setLeafPredictionStrategy(SelectedTag) - Method in class weka.classifiers.trees.HoeffdingTree

Set the leaf prediction strategy to use (majority class, naive Bayes or naive Bayes adaptive)

setLearningRate(double) - Method in class weka.classifiers.functions.MultilayerPerceptron

The learning rate can be set using this command.

setLearningRate(double) - Method in class weka.classifiers.functions.SGD

Set the learning rate.

setLearningRate(double) - Method in class weka.classifiers.functions.SGDText

Set the learning rate.

setLeftMargin(Double) - Method in class weka.core.pmml.jaxbbindings.Interval

Sets the value of the leftMargin property.

setLegendText(Vector<String>) - Method in class weka.gui.beans.ChartEvent

Set the legend text vector

setLength(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextDocument

Sets the value of the length property.

setLength(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Sets the value of the length property.

setLengthLimit(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the lengthLimit property.

setLevel(Level) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Sets the value of the level property.

setLeverage(Float) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the leverage property.

setLift(Float) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the lift property.

setLift(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the lift property.

setLiftData(LiftData) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the liftData property.

setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph

Sets the value of the liftGraph property.

setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph

Sets the value of the liftGraph property.

setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph

Sets the value of the liftGraph property.

setLikelihoodThreshold(double) - Method in class weka.classifiers.meta.LogitBoost

Set the value of Precision.

setLinkFunction(LINKFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the linkFunction property.

setLinkParameter(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the linkParameter property.

setLinkType(SelectedTag) - Method in class weka.clusterers.HierarchicalClusterer

setListData(Object[]) - Method in class weka.gui.CheckBoxList

Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.

setListData(Vector) - Method in class weka.gui.CheckBoxList

Constructs a CheckBoxListModel from a Vector and then applies setModel to it.

setLNorm(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set the L-norm to used

setLNorm(double) - Method in class weka.classifiers.functions.SGDText

Set the L-norm to used

setLoadClassifierFileName(String) - Method in class weka.gui.beans.Classifier

Set the name of the classifier to load at execution time.

setLoaded(boolean) - Method in class weka.gui.beans.AttributeSummarizer

Set whether this perspective is "loaded" - i.e.

setLoaded(boolean) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Set whether this perspective is "loaded" - i.e.

setLoaded(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setLoaded(boolean) - Method in class weka.gui.beans.ScatterPlotMatrix

Set whether this perspective is "loaded" - i.e.

setLoaded(boolean) - Method in class weka.gui.beans.SQLViewerPerspective

Set whether this perspective is "loaded" - i.e.

setLoader(Loader) - Method in class weka.gui.beans.Loader

Set the loader to use

setLocallyPredictive(boolean) - Method in class weka.attributeSelection.CfsSubsetEval

Include locally predictive attributes

setLocalTermWeights(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization

Sets the value of the localTermWeights property.

setLocalTransformations(LocalTransformations) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the localTransformations property.

setLocalTransformations(LocalTransformations) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the localTransformations property.

setLocationProbs(int, double[]) - Method in class weka.gui.boundaryvisualizer.RemoteResult

Store the classifier's distribution for a particular pixel in the visualization

setLog(Logger) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Set a logger to use.

setLog(Debug.Log) - Method in class weka.core.Debug.Random

the log to use, if it is null then stdout is used

setLog(Logger) - Method in interface weka.core.LogHandler

Set the log to use

setLog(Logger) - Method in interface weka.core.pmml.PMMLModel

Set a logger to use.

setLog(Logger) - Method in class weka.gui.beans.AbstractDataSink

Set a log for this bean

setLog(Logger) - Method in class weka.gui.beans.AbstractEvaluator

Set a logger

setLog(Logger) - Method in class weka.gui.beans.AbstractTestSetProducer

Set a logger

setLog(Logger) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Set a log for this bean

setLog(Logger) - Method in class weka.gui.beans.AbstractTrainingSetProducer

Set a logger

setLog(Logger) - Method in class weka.gui.beans.Appender

Set a logger

setLog(Logger) - Method in class weka.gui.beans.Associator

Set a logger

setLog(Logger) - Method in interface weka.gui.beans.BeanCommon

Set a logger

setLog(Logger) - Method in class weka.gui.beans.ClassAssigner

setLog(Logger) - Method in class weka.gui.beans.Classifier

Set a logger

setLog(Logger) - Method in class weka.gui.beans.ClassValuePicker

setLog(Logger) - Method in class weka.gui.beans.Clusterer

Set a logger

setLog(Logger) - Method in class weka.gui.beans.CostBenefitAnalysis

Set a logger

setLog(Logger) - Method in class weka.gui.beans.DataVisualizer

Set a logger

setLog(Logger) - Method in class weka.gui.beans.Filter

Set a logger

setLog(Logger) - Method in class weka.gui.beans.FlowByExpression

setLog(Logger) - Method in class weka.gui.beans.FlowRunner

setLog(Logger) - Method in class weka.gui.beans.ImageSaver

setLog(Logger) - Method in class weka.gui.beans.ImageViewer

setLog(Logger) - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Set a logger

setLog(Logger) - Method in class weka.gui.beans.Join

Set a log to use

setLog(Logger) - Method in class weka.gui.beans.Loader

Set a logger

setLog(Logger) - Method in interface weka.gui.beans.LogWriter

Set a logger

setLog(Logger) - Method in class weka.gui.beans.MetaBean

Set a logger

setLog(Logger) - Method in class weka.gui.beans.ModelPerformanceChart

Set a logger

setLog(Logger) - Method in class weka.gui.beans.PredictionAppender

Set a logger

setLog(Logger) - Method in class weka.gui.beans.SerializedModelSaver

Set a log for this bean.

setLog(Logger) - Method in class weka.gui.beans.Sorter

Set a logger

setLog(Logger) - Method in class weka.gui.beans.StripChart

Set a logger

setLog(Logger) - Method in class weka.gui.beans.SubstringLabeler

Set a logger

setLog(Logger) - Method in class weka.gui.beans.SubstringReplacer

Set a logger

setLog(Logger) - Method in class weka.gui.beans.TextSaver

setLog(Logger) - Method in class weka.gui.beans.TextViewer

Set a logger

setLog(Logger) - Method in class weka.gui.explorer.AssociationsPanel

Sets the Logger to receive informational messages

setLog(Logger) - Method in class weka.gui.explorer.AttributeSelectionPanel

Sets the Logger to receive informational messages

setLog(Logger) - Method in class weka.gui.explorer.ClassifierPanel

Sets the Logger to receive informational messages.

setLog(Logger) - Method in class weka.gui.explorer.ClustererPanel

Sets the Logger to receive informational messages

setLog(Logger) - Method in class weka.gui.explorer.DataGeneratorPanel

Sets the Logger to receive informational messages

setLog(Logger) - Method in interface weka.gui.explorer.Explorer.LogHandler

Sets the Logger to receive informational messages

setLog(Logger) - Method in class weka.gui.explorer.PreprocessPanel

Sets the Logger to receive informational messages

setLog(Logger) - Method in class weka.gui.visualize.VisualizePanel

Sets the Logger to receive informational messages

setLookAndFeel(String) - Static method in class weka.gui.LookAndFeel

sets the look and feel to the specified class

setLookAndFeel() - Static method in class weka.gui.LookAndFeel

sets the look and feel to the one in the props-file or if not set the default one of the system

setLookupCacheSize(int) - Method in class weka.attributeSelection.BestFirst

Set the maximum size of the evaluated subset cache (hashtable).

setLossFunction(SelectedTag) - Method in class weka.classifiers.functions.SGD

Set the loss function to use.

setLossFunction(SelectedTag) - Method in class weka.classifiers.functions.SGDText

Set the loss function to use.

setLower(double) - Method in class weka.core.pmml.jaxbbindings.UniformDistribution

Sets the value of the lower property.

setLowerBoundMinSupport(double) - Method in class weka.associations.Apriori

Set the value of lowerBoundMinSupport.

setLowerBoundMinSupport(double) - Method in class weka.associations.FPGrowth

Set the value of lowerBoundMinSupport.

setLowercaseTokens(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set whether to convert all tokens to lowercase

setLowercaseTokens(boolean) - Method in class weka.classifiers.functions.SGDText

Set whether to convert all tokens to lowercase

setLowerCaseTokens(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the tokens are to be downcased or not.

setLowerSize(int) - Method in class weka.experiment.LearningRateResultProducer

Set the value of LowerSize.

setLowValue(Double) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the lowValue property.

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.AttributeSummarizer

Set a reference to the main KnowledgeFlow perspective - i.e.

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective

Set a reference to the main KnowledgeFlow perspective - i.e.

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.ScatterPlotMatrix

Set a reference to the main KnowledgeFlow perspective - i.e.

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.SQLViewerPerspective

Set a reference to the main KnowledgeFlow perspective - i.e.

setMakeBinary(boolean) - Method in class weka.filters.supervised.attribute.Discretize

Sets whether binary attributes should be made for discretized ones.

setMakeBinary(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets whether binary attributes should be made for discretized ones.

setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.Apply

Sets the value of the mapMissingTo property.

setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.Discretize

Sets the value of the mapMissingTo property.

setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.FieldRef

Sets the value of the mapMissingTo property.

setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the mapMissingTo property.

setMapMissingTo(Double) - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Sets the value of the mapMissingTo property.

setMapMissingTo(Double) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Sets the value of the mapMissingTo property.

setMappedValue(String) - Method in class weka.core.pmml.jaxbbindings.Item

Sets the value of the mappedValue property.

setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the mapValues property.

setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the mapValues property.

setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the mapValues property.

setMargin(int, double[]) - Method in class weka.classifiers.bayes.net.EditableBayesNet

set marginal distibution for a node

setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D

Set the master plot.

setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel

Set the master plot for the visualize panel

setMatch(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Set the string/regex to use for matching

setMatch(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Set the string/regex to use for matching

setMatchAttributeName(String) - Method in class weka.gui.beans.SubstringLabeler

setMatchDetails(String) - Method in class weka.gui.beans.SubstringLabeler

Set internally encoded list of match rules

setMatchMissingValues(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Sets whether missing values are counted as a match.

setMatchReplaceDetails(String) - Method in class weka.gui.beans.SubstringReplacer

Set internally encoded list of match-replace rules

setMatrix(int, int, int, int, Matrix) - Method in class weka.core.matrix.Matrix

Set a submatrix.

setMatrix(int[], int[], Matrix) - Method in class weka.core.matrix.Matrix

Set a submatrix.

setMatrix(int[], int, int, Matrix) - Method in class weka.core.matrix.Matrix

Set a submatrix.

setMatrix(int, int, int[], Matrix) - Method in class weka.core.matrix.Matrix

Set a submatrix.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Comparisons

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.CorrelationValues

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Covariances

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix

Sets the value of the matrix property.

setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Predictor

Sets the value of the matrix property.

setMax(Double) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the max property.

setMax(Double) - Method in class weka.core.pmml.jaxbbindings.Time

Sets the value of the max property.

setMax(double) - Method in class weka.gui.beans.ChartEvent

Set the max y value

setMaxBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of maxBoostingIterations.

setMaxCardinality(int) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

sets the cardinality

setMaxCount(double) - Method in class weka.filters.supervised.instance.SpreadSubsample

Sets the value for the max count

setMaxDecimalPlaces(int) - Method in class weka.core.converters.ArffSaver

Set the maximum number of decimal places to print

setMaxDecimalPlaces(int) - Method in class weka.core.converters.CSVSaver

Set the maximum number of decimal places to print

setMaxDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the naximum default.

setMaxDepth(int) - Method in class weka.classifiers.trees.RandomForest

Set the maximum depth of the tree, 0 for unlimited.

setMaxDepth(int) - Method in class weka.classifiers.trees.RandomTree

Set the maximum depth of the tree, 0 for unlimited.

setMaxDepth(int) - Method in class weka.classifiers.trees.REPTree

Set the value of MaxDepth.

setMaximum(Double) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the maximum property.

setMaximum(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the maximum property.

setMaximumAntConsSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumAntConsSeparationTime property.

setMaximumAttributeNames(int) - Method in class weka.attributeSelection.PrincipalComponents

Sets maximum number of attributes to include in transformed attribute names.

setMaximumAttributeNames(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Sets maximum number of attributes to include in transformed attribute names.

setMaximumAttributes(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Sets maximum number of PC attributes to retain.

setMaximumItemsetSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumItemsetSeparationTime property.

setMaximumNumberOfAntecedentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumNumberOfAntecedentItems property.

setMaximumNumberOfClusters(int) - Method in class weka.clusterers.EM

Set the maximum number of clusters to consider when cross-validating

setMaximumNumberOfConsequentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumNumberOfConsequentItems property.

setMaximumNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumNumberOfItems property.

setMaximumTotalSequenceTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the maximumTotalSequenceTime property.

setMaximumVariancePercentageAllowed(double) - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Sets the maximum variance attributes are allowed to have before they are deleted by the filter.

setMaxInstancesInLeaf(int) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets the maximum number of instances allowed in a leaf.

setMaxInstancesInLeaf(int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the maximum number of instances allowed in a leaf.

setMaxInstInLeaf(int) - Method in class weka.core.neighboursearch.KDTree

Sets the maximum number of instances in a leaf.

setMaxInstNum(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the upper boundary for instances per cluster.

setMaxInstNum(int) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the upper boundary for instances per cluster.

setMaxIteration(int) - Method in class weka.core.Optimization

Set the maximal number of iterations in searching (Default 200)

setMaxIterations(int) - Method in class weka.classifiers.trees.lmt.LogisticBase

Sets the parameter "maxIterations".

setMaxIterations(int) - Method in class weka.clusterers.EM

Set the maximum number of iterations to perform

setMaxIterations(int) - Method in class weka.clusterers.SimpleKMeans

set the maximum number of iterations to be executed.

setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed

setMaxIts(int) - Method in class weka.classifiers.functions.Logistic

Set the value of MaxIts.

setMaxK(int) - Method in class weka.classifiers.functions.VotedPerceptron

Set the value of maxK.

setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Sets the max number of parents

setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.K2

Sets the max number of parents

setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Sets the max number of parents

setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.K2

Sets the max number of parents

setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Sets the max number of parents

setMaxNumberOfItems(int) - Method in class weka.associations.FPGrowth

Set the maximum number of items to include in large items sets.

setMaxNumberOfItemsPerTA(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the maxNumberOfItemsPerTA property.

setMaxNumberOfItemsPerTransaction(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the maxNumberOfItemsPerTransaction property.

setMaxNumberOfTAsPerTAGroup(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the maxNumberOfTAsPerTAGroup property.

setMaxNumCandidateCanopiesToHoldInMemory(int) - Method in class weka.clusterers.Canopy

Set the maximum number of candidate canopies to retain in memory during training.

setMaxPlots(int) - Method in class weka.gui.beans.AttributeSummarizer

Set the maximum number of plots to display

setMaxRadius(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the upper boundary for the radiuses of the clusters.

setMaxRange(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Sets the upper boundary for the range of x

setMaxRelativeLeafRadius(double) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Sets the maximum relative radius, allowed for a leaf node.

setMaxRows(int) - Method in class weka.gui.sql.QueryPanel

sets the maximum number of rows to display.

setMaxRuleSize(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the maximum number of tests in rules.

setMaxSubsequenceLength(int) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets the maximum length of the subsequence.

setMaxThreshold(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the maximum threshold.

setMaxTime(Double) - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables

Sets the value of the maxTime property.

setMaxTime(double) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Sets the value of the maxTime property.

setMDLTheoryWeight(double) - Method in class weka.classifiers.rules.RuleStats

Set the weight of theory in MDL calcualtion

setMean(double) - Method in class weka.core.pmml.jaxbbindings.AnyDistribution

Sets the value of the mean property.

setMean(double) - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution

Sets the value of the mean property.

setMean(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the mean property.

setMean(double) - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution

Sets the value of the mean property.

setMean(Double) - Method in class weka.core.pmml.jaxbbindings.Time

Sets the value of the mean property.

setMean(int, int, double) - Method in class weka.experiment.ResultMatrix

sets the mean at the given position (if the position is valid).

setMeanAbsoluteError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the meanAbsoluteError property.

setMeanError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the meanError property.

setMeanOfSquares(Double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the meanOfSquares property.

setMeanPrec(int) - Method in class weka.experiment.ResultMatrix

sets the precision for the means.

setMeanSquared(boolean) - Method in class weka.classifiers.lazy.IBk

Sets whether the mean squared error is used rather than mean absolute error when doing cross-validation.

setMeanSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the meanSquaredError property.

setMeanStddev(String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets mean and standarddeviation.

setMeanWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the mean (0 = optimal).

setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.BallTree

Sets whether to calculate the performance statistics or not.

setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.KDTree

Sets whether to calculate the performance statistics or not.

setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Sets whether to calculate the performance statistics or not.

setMedian(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the median property.

setMergeValueRange(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Sets range of the merge values used.

setMetaClassifier(Classifier) - Method in class weka.classifiers.meta.Stacking

Adds meta classifier

setMethod(NeuralMethod) - Method in class weka.classifiers.functions.neural.NeuralNode

Set how this node should operate (note that the neural method has no internal state, so the same object can be used by any number of nodes.

setMethod(SelectedTag) - Method in class weka.classifiers.meta.MultiClassClassifier

Sets the method used.

setMethod(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Sets the value of the method property.

setMethodName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Set the transformation method.

setMetricsToDisplay(List<String>) - Method in class weka.classifiers.evaluation.Evaluation

Set a list of the names of metrics to have appear in the output.

setMetricsToDisplay(List<String>) - Method in class weka.classifiers.Evaluation

Set a list of the names of metrics to have appear in the output.

setMetricType(SelectedTag) - Method in class weka.associations.Apriori

Set the metric type for ranking rules

setMetricType(SelectedTag) - Method in class weka.associations.FPGrowth

Set the metric type to use.

setMin(Double) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the min property.

setMin(Double) - Method in class weka.core.pmml.jaxbbindings.Time

Sets the value of the min property.

setMin(double) - Method in class weka.gui.beans.ChartEvent

Set the min y value

setMinBoxRelWidth(double) - Method in class weka.core.neighboursearch.KDTree

Sets the minimum relative box width.

setMinBucketSize(int) - Method in class weka.classifiers.rules.OneR

Set the value of minBucketSize.

setMinDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the minimum default.

setMinimal(boolean) - Method in class weka.classifiers.functions.LinearRegression

Sets whether to be more memory conservative or being able to output the model as string.

setMinimizeAbsoluteError(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization

Sets whether to min.

setMinimizeExpectedCost(boolean) - Method in class weka.classifiers.meta.CostSensitiveClassifier

Set the value of MinimizeExpectedCost.

setMinimum(Double) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the minimum property.

setMinimum(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the minimum property.

setMinimumAntConsSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumAntConsSeparationTime property.

setMinimumBucketSize(int) - Method in class weka.attributeSelection.OneRAttributeEval

Set the minumum bucket size used by OneR

setMinimumCanopyDensity(double) - Method in class weka.clusterers.Canopy

Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.

setMinimumConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the minimumConfidence property.

setMinimumConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumConfidence property.

setMinimumFractionOfWeightInfoGain(double) - Method in class weka.classifiers.trees.HoeffdingTree

Set the minimum fraction of weight required down at least two branches for info gain splitting

setMinimumFrequency(int) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Sets the minimum frequency.

setMinimumItemsetSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumItemsetSeparationTime property.

setMinimumLift(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumLift property.

setMinimumNumberInstances(int) - Method in class weka.core.Capabilities

sets the minimum number of instances that have to be in the dataset

setMinimumNumberOfAntecedentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumNumberOfAntecedentItems property.

setMinimumNumberOfConsequentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumNumberOfConsequentItems property.

setMinimumNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumNumberOfItems property.

setMinimumSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the minimumSupport property.

setMinimumSupport(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumSupport property.

setMinimumTotalSequenceTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints

Sets the value of the minimumTotalSequenceTime property.

setMiningBuildTask(MiningBuildTask) - Method in class weka.core.pmml.jaxbbindings.PMML

Sets the value of the miningBuildTask property.

setMiningModel(MiningModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the miningModel property.

setMinInstNum(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the lower boundary for instances per cluster.

setMinInstNum(int) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the lower boundary for instances per cluster.

setMinkowski(Minkowski) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the minkowski property.

setMinLogLikelihoodImprovementCV(double) - Method in class weka.clusterers.EM

Set the minimum improvement in cross-validated log likelihood required to consider increasing the number of clusters when cross-validating to find the best number of clusters

setMinLogLikelihoodImprovementIterating(double) - Method in class weka.clusterers.EM

Set the minimum improvement in log likelihood necessary to perform another iteration of the E and M steps.

setMinMaxX(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the minimum and maximum values of the x axis fixed dimension

setMinMaxY(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the minimum and maximum values of the y axis fixed dimension

setMinMetric(double) - Method in class weka.associations.Apriori

Set the value of minConfidence.

setMinMetric(double) - Method in class weka.associations.FPGrowth

Set the value of minConfidence.

setMinNo(double) - Method in class weka.classifiers.rules.JRip

Sets the minimum total weight of the instances in a rule

setMinNum(double) - Method in class weka.classifiers.trees.RandomTree

Set the value of MinNum.

setMinNum(double) - Method in class weka.classifiers.trees.REPTree

Set the value of MinNum.

setMinNumInstances(int) - Method in class weka.classifiers.trees.LMT

Set the value of minNumInstances.

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.M5Base

Set the minimum number of instances to allow at a leaf node

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.Rule

Set the minumum number of instances to allow at a leaf node

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.RuleNode

Set the minumum number of instances to allow at a leaf node

setMinNumObj(int) - Method in class weka.classifiers.rules.PART

Set the value of minNumObj.

setMinNumObj(int) - Method in class weka.classifiers.trees.J48

Set the value of minNumObj.

setMinRadius(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the lower boundary for the radiuses of the clusters.

setMinRange(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Sets the lower boundary for the range of x

setMinRuleSize(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the minimum number of tests in rules.

setMinStdDev(double) - Method in class weka.clusterers.EM

Set the minimum value for standard deviation when calculating normal density.

setMinStdDev(double) - Method in class weka.clusterers.MakeDensityBasedClusterer

Set the minimum value for standard deviation when calculating normal density.

setMinStdDevPerAtt(double[]) - Method in class weka.clusterers.EM

setMinTermFreq(int) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Set the MinTermFreq value.

setMinThreshold(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Set the minimum threshold.

setMinVarianceProp(double) - Method in class weka.classifiers.trees.RandomTree

Set the value of MinVarianceProp.

setMinVarianceProp(double) - Method in class weka.classifiers.trees.REPTree

Set the value of MinVarianceProp.

setMinWordFrequency(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set the minimum word frequency.

setMinWordFrequency(double) - Method in class weka.classifiers.functions.SGDText

Set the minimum word frequency.

setMissing(int) - Method in class weka.core.AbstractInstance

Sets a specific value to be "missing".

setMissing(Attribute) - Method in class weka.core.AbstractInstance

Sets a specific value to be "missing".

setMissing(int) - Method in interface weka.core.Instance

Sets a specific value to be "missing".

setMissing(Attribute) - Method in interface weka.core.Instance

Sets a specific value to be "missing".

setMissingFreq(Double) - Method in class weka.core.pmml.jaxbbindings.Counts

Sets the value of the missingFreq property.

setMissingMerge(boolean) - Method in class weka.attributeSelection.GainRatioAttributeEval

distribute the counts for missing values across observed values

setMissingMerge(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval

distribute the counts for missing values across observed values

setMissingMerge(boolean) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

distribute the counts for missing values across observed values

setMissingMode(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Set the missing value mode.

setMissingMode(SelectedTag) - Method in class weka.classifiers.lazy.KStar

Sets the method to use for handling missing values.

setMissingSeparate(boolean) - Method in class weka.attributeSelection.CfsSubsetEval

Treat missing as a separate value

setMissingValue(String) - Method in class weka.core.converters.CSVLoader

Sets the placeholder for missing values.

setMissingValue(String) - Method in class weka.core.converters.CSVSaver

Sets the placeholder for missing values.

setMissingValuePenalty(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the missingValuePenalty property.

setMissingValuePenalty(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the missingValuePenalty property.

setMissingValueReplacement(String) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the missingValueReplacement property.

setMissingValuesReplacer(Filter) - Method in class weka.clusterers.Canopy

Set a ready-to-use missing values replacement filter

setMissingValueStrategy(MISSINGVALUESTRATEGY) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the missingValueStrategy property.

setMissingValueStrategy(MISSINGVALUESTRATEGY) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the missingValueStrategy property.

setMissingValueTreatment(MISSINGVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the missingValueTreatment property.

setModalValue(String) - Method in class weka.core.pmml.jaxbbindings.DiscrStats

Sets the value of the modalValue property.

setModel(Classifier) - Method in class weka.classifiers.misc.SerializedClassifier

Sets the fully built model to use, if one doesn't want to load a model from a file or already deserialized a model from somewhere else.

setModel(TableModel) - Method in class weka.gui.arffviewer.ArffTable

sets the new model

setModel(ListModel) - Method in class weka.gui.CheckBoxList

sets the model - must be an instance of CheckBoxListModel

setModel(TableModel) - Method in class weka.gui.SortedTableModel

sets the model to use

setModelClass(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the modelClass property.

setModelDF(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the modelDF property.

setModelFile(File) - Method in class weka.classifiers.misc.SerializedClassifier

Sets the file containing the serialized model.

setModelHeader(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier

Set the structure of the data used to create the model.

setModelLiftGraph(ModelLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the modelLiftGraph property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.BaselineModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.MiningModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel

Sets the value of the modelName property.

setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the modelName property.

setModelPath(String) - Method in class weka.classifiers.misc.InputMappedClassifier

Set the path from which to load a model.

setModelStats(ModelStats) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the modelStats property.

setModelStats(ModelStats) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the modelStats property.

setModelType(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the modelType property.

setModelType(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the modelType property.

setModePanel(SetupModePanel) - Method in class weka.gui.experiment.SimpleSetupPanel

Sets the panel used to switch between simple and advanced modes.

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.AssociatorCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.AttributeSummarizerCustomizer

Set a listener interested in whether we've modified the ImageSaver that we're customizing

setModifiedListener(BeanCustomizer.ModifyListener) - Method in interface weka.gui.beans.BeanCustomizer

Set a listener to be notified about the modified status of this object

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassAssignerCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassifierCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClustererCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.DataVisualizerCustomizer

Set a listener interested in whether we've modified the ImageSaver that we're customizing

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.FilterCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.FlowByExpressionCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ImageSaverCustomizer

Set a listener interested in whether we've modified the ImageSaver that we're customizing

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.JoinCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.LoaderCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer

Set a listener interested in whether we've modified the ImageSaver that we're customizing

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.NoteCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SaverCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SorterCustomizer

The modify listener interested in any chages we might make

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SubstringLabelerCustomizer

Set a listener interested in knowing if the object being edited has changed.

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SubstringReplacerCustomizer

Set a listener interested in knowing if the object being edited has changed.

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.TextSaverCustomizer

Set a listener interested in whether we've modified the TextSaver that we're customizing

setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.filters.AddUserFieldsCustomizer

Set an object that is interested in knowing when we make a change to the object that we're editing

setModifiedStatus(Object, boolean) - Method in interface weka.gui.beans.BeanCustomizer.ModifyListener

Tell the listener about the modified status of the source object.

setModifiedStatus(Object, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp

Tells us about the modified status of a particular object - typically a customizer that is editing a flow component.

setModifyHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Sets whether the header will be modified when selecting on nominal attributes.

setModifyHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Sets whether the header will be modified when selecting on nominal attributes.

setMomentum(double) - Method in class weka.classifiers.functions.MultilayerPerceptron

The momentum can be set using this command.

setMultiInstance(boolean) - Method in class weka.core.TestInstances

sets whether multi-instance data should be generated (with a fixed data structure)

setMultiLineComment(boolean) - Method in class weka.gui.scripting.SyntaxDocument

Sets whether to enable multi-line comments.

setMultiLineCommentEnd(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the string that is the end of a multi-line comment.

setMultiLineCommentStart(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the string that is the start of a multi-line comment.

setMultipleModelMethod(MULTIPLEMODELMETHOD) - Method in class weka.core.pmml.jaxbbindings.Segmentation

Sets the value of the multipleModelMethod property.

setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ArrayType

Sets the value of the n property.

setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.INTSparseArray

Sets the value of the n property.

setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.REALSparseArray

Sets the value of the n property.

setNaiveBayesModel(NaiveBayesModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the naiveBayesModel property.

setNaiveBayesPredictionThreshold(double) - Method in class weka.classifiers.trees.HoeffdingTree

Set the number of instances (weight) a leaf should observe before allowing naive Bayes to make predictions

setName(String) - Method in class weka.core.pmml.jaxbbindings.Application

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Characteristic

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Extension

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Parameter

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.ParameterField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Partition

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Predictor

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.PredictorTerm

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.Taxonomy

Sets the value of the name property.

setName(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument

Sets the value of the name property.

setName(String) - Method in class weka.filters.unsupervised.attribute.AddExpression

Set the name for the new attribute.

setName(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Set the name of the new attribute

setName(String) - Method in class weka.gui.visualize.VisualizePanel

Set a name for this plot

setNbCols(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Matrix

Sets the value of the nbCols property.

setNbCorrect(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet

Sets the value of the nbCorrect property.

setNbCorrect(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the nbCorrect property.

setNbRows(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Matrix

Sets the value of the nbRows property.

setNearestNeighborModel(NearestNeighborModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the nearestNeighborModel property.

setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.IBk

Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).

setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.LWL

Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).

setNegativeTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC

Sets the value of the negativeTargetFieldDisplayValue property.

setNegativeTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC

Sets the value of the negativeTargetFieldValue property.

setNeuralNetwork(NeuralNetwork) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the neuralNetwork property.

setNewAttributeName(String) - Method in class weka.gui.beans.SubstringLabelerRules

Set the name to use for the new attribute that is added

setNGramMaxSize(int) - Method in class weka.core.tokenizers.NGramTokenizer

Sets the max size of the Ngram.

setNGramMinSize(int) - Method in class weka.core.tokenizers.NGramTokenizer

Sets the min size of the Ngram.

setNoClass(boolean) - Method in class weka.core.TestInstances

whether to have no class, e.g., for clusterers; otherwise the class attribute index is set to last

setNode(Node) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the node property.

setNodeName(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet

change the name of a node

setNodesEdges(ArrayList<GraphNode>, ArrayList<GraphEdge>) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

Sets the nodes and edges for this LayoutEngine.

setNodesEdges(ArrayList<GraphNode>, ArrayList<GraphEdge>) - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method sets the nodes and edges vectors of the LayoutEngine

setNodeSize(int, int) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

Sets the size of a node.

setNodeSize(int, int) - Method in interface weka.gui.graphvisualizer.LayoutEngine

This method sets the allowed size of the node

setNodeSplitter(KDTreeNodeSplitter) - Method in class weka.core.neighboursearch.KDTree

Sets the splitting method to use to split the nodes of the KDTree.

setNodeWidthNormalization(boolean) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Sets whether if a nodes region is normalized or not.

setNoHeaderRow(boolean) - Method in class weka.core.converters.CSVSaver

Set whether to not write the header row

setNoHeaderRowPresent(boolean) - Method in class weka.core.converters.CSVLoader

Set whether there is no header row in the data.

setNoise(double) - Method in class weka.classifiers.functions.GaussianProcesses

Set the level of Gaussian Noise.

setNoisePercent(double) - Method in class weka.datagenerators.classifiers.classification.LED24

Sets the noise percentage.

setNoiseRate(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Sets the gaussian noise rate.

setNoiseRate(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the percentage of noise set.

setNoiseRate(double) - Method in class weka.datagenerators.clusterers.SubspaceCluster

Sets the percentage of noise set.

setNoiseVariance(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Sets the noise variance

setNominalAttributes(String) - Method in class weka.core.converters.CSVLoader

Sets the attribute range to be forced to type nominal.

setNominalBinary(boolean) - Method in class weka.gui.beans.SubstringLabeler

Set whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.

setNominalBinary(boolean) - Method in class weka.gui.beans.SubstringLabelerRules

Set whether to create a nominal binary attribute in the case when the user has not supplied an explicit label to use for each rule.

setNominalCols(Range) - Method in class weka.datagenerators.ClusterGenerator

Sets which attributes are nominal.

setNominalIndices(String) - Method in class weka.datagenerators.ClusterGenerator

Sets which attributes are nominal

setNominalIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Set which nominal labels are to be included in the selection.

setNominalIndicesArr(int[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Set which values of a nominal attribute are to be used for selection.

setNominalLabels(String) - Method in class weka.filters.unsupervised.attribute.Add

Set the labels for nominal attribute creation.

setNominalLabelSpecs(Object[]) - Method in class weka.core.converters.CSVLoader

Set label specifications for nominal attributes.

setNominalStringReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Set the nominal/string replacement value

setNominalToBinaryFilter(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

setNoPruning(boolean) - Method in class weka.classifiers.trees.REPTree

Set the value of NoPruning.

setNoReplacement(boolean) - Method in class weka.filters.supervised.instance.Resample

Sets whether instances are drawn with or with out replacement.

setNoReplacement(boolean) - Method in class weka.filters.unsupervised.instance.Resample

Sets whether instances are drawn with or with out replacement.

setNorm(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set the norm of the instances

setNorm(double) - Method in class weka.classifiers.functions.SGDText

Set the norm of the instances

setNorm(double) - Method in class weka.core.pmml.jaxbbindings.LinearNorm

Sets the value of the norm property.

setNormalizationMethod(NNNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the normalizationMethod property.

setNormalizationMethod(NNNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the normalizationMethod property.

setNormalizationMethod(REGRESSIONNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the normalizationMethod property.

setNormalizationMethod(REGRESSIONNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the normalizationMethod property.

setNormalizationScheme(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the normalizationScheme property.

setNormalizeAttributes(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

setNormalizedCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the normalizedCountTable property.

setNormalizeDimWidths(boolean) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Should we normalize the widths(ranges) of the dimensions (attributes) before selecting the widest one.

setNormalizeDocLength(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set whether to normalize the length of each document

setNormalizeDocLength(boolean) - Method in class weka.classifiers.functions.SGDText

Set whether to normalize the length of each document

setNormalizeDocLength(SelectedTag) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the word frequencies for a document (instance) should be normalized or not.

setNormalizeNodeWidth(boolean) - Method in class weka.core.neighboursearch.KDTree

Sets the flag for normalizing the widths of a KDTree Node by the width of the dimension in the universe.

setNormalizeNumericClass(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the normContinuous property.

setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the normContinuous property.

setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the normContinuous property.

setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the normDiscrete property.

setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the normDiscrete property.

setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the normDiscrete property.

setNoSizeDetermination(boolean) - Method in class weka.experiment.ClassifierSplitEvaluator

Sets whether the size determination (train/test/classifer) is skipped.

setNoSizeDetermination(boolean) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Sets whether the size determination (train/test/clusterer) is skipped.

setNoSizeDetermination(boolean) - Method in class weka.experiment.RegressionSplitEvaluator

Sets whether the size determination (train/test/classifer) is skipped.

setNotCapabilities(Capabilities) - Method in class weka.core.FindWithCapabilities

Uses the given "not to have" Capabilities for the search.

setNotes(String) - Method in class weka.experiment.Experiment

Set the user notes.

setNotes(String) - Method in class weka.experiment.RemoteExperiment

Set the user notes.

setNoteText(String) - Method in class weka.gui.beans.Note

Set the text to display

setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel

sets whether the notification of changes is enabled

setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel

sets whether the notification of changes is enabled

setNoTrueChildStrategy(NOTRUECHILDSTRATEGY) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the noTrueChildStrategy property.

setNoTrueChildStrategy(NOTRUECHILDSTRATEGY) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the noTrueChildStrategy property.

setNrOfGoodOperations(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Sets the number of "good operations"

setNrOfLookAheadSteps(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Sets the number of look-ahead steps

setNumAllConds(double) - Method in class weka.classifiers.rules.RuleStats

Set the number of all conditions that could appear in a rule in this RuleStats object, if the number set is smaller than 0 (typically -1), then it calcualtes based on the data store

setNumArcs(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet

Sets the number of arcs for the bayesian net

setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet

Sets the number of attributes the dataset should have.

setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Sets the number of attributes the dataset should have.

setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the number of attributes the dataset should have.

setNumAttributes(int) - Method in class weka.datagenerators.clusterers.SubspaceCluster

Sets the number of attributes the dataset should have.

setNumAttributes(int) - Method in class weka.datagenerators.ClusterGenerator

Sets the number of attributes the dataset should have.

setNumAttributes(double) - Method in class weka.filters.unsupervised.attribute.RandomSubset

Set the number of attributes.

setNumberOfAttributes(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Sets the value of the numberOfAttributes property.

setNumberOfAttributes(int) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets the number of attributes (dimensions) the data should be reduced to

setNumberOfClusters(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel

Sets the value of the numberOfClusters property.

setNumberOfCoefficients(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Coefficients

Sets the value of the numberOfCoefficients property.

setNumberOfDocuments(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the numberOfDocuments property.

setNumberOfFields(BigInteger) - Method in class weka.core.pmml.jaxbbindings.DataDictionary

Sets the value of the numberOfFields property.

setNumberOfFields(BigInteger) - Method in class weka.core.pmml.jaxbbindings.VectorFields

Sets the value of the numberOfFields property.

setNumberOfInputs(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralInputs

Sets the value of the numberOfInputs property.

setNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the numberOfItems property.

setNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Itemset

Sets the value of the numberOfItems property.

setNumberOfItemsets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the numberOfItemsets property.

setNumberOfLayers(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the numberOfLayers property.

setNumberOfNeighbors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the numberOfNeighbors property.

setNumberOfNeurons(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the numberOfNeurons property.

setNumberOfOutputs(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs

Sets the value of the numberOfOutputs property.

setNumberOfRules(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the numberOfRules property.

setNumberOfSets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the numberOfSets property.

setNumberOfSets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the numberOfSets property.

setNumberOfSupportVectors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SupportVectors

Sets the value of the numberOfSupportVectors property.

setNumberOfTerms(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextModel

Sets the value of the numberOfTerms property.

setNumberOfTransactionGroups(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the numberOfTransactionGroups property.

setNumberOfTransactions(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel

Sets the value of the numberOfTransactions property.

setNumberOfTransactions(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel

Sets the value of the numberOfTransactions property.

setNumberOfVectors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Sets the value of the numberOfVectors property.

setNumBins(int) - Method in class weka.classifiers.meta.RegressionByDiscretization

Sets the number of bins to divide each selected numeric attribute into

setNumBins(int) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats

setNumBins(int) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Sets the number of bins

setNumBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of numBoostingIterations.

setNumBoostingIterations(int) - Method in class weka.classifiers.trees.LMT

Set the value of numBoostingIterations.

setNumCentroids(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Sets the number of centroids to use.

setNumClasses(int) - Method in class weka.core.TestInstances

sets the number of classes

setNumClasses(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Sets the number of classes the dataset should have.

setNumClasses(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the number of classes the dataset should have.

setNumClusters(int) - Method in class weka.clusterers.Canopy

setNumClusters(int) - Method in class weka.clusterers.EM

Set the number of clusters (-1 to select by CV).

setNumClusters(int) - Method in class weka.clusterers.FarthestFirst

set the number of clusters to generate

setNumClusters(int) - Method in class weka.clusterers.HierarchicalClusterer

setNumClusters(int) - Method in class weka.clusterers.MakeDensityBasedClusterer

Set the number of clusters to generate.

setNumClusters(int) - Method in interface weka.clusterers.NumberOfClustersRequestable

Set the number of clusters to generate

setNumClusters(int) - Method in class weka.clusterers.SimpleKMeans

set the number of clusters to generate.

setNumClusters(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the number of clusters the dataset should have.

setNumCycles(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the the number of cycles.

setNumDate(int) - Method in class weka.core.CheckScheme

sets the number of data attributes

setNumDate(int) - Method in class weka.core.TestInstances

sets the number of date attributes

setNumDecimals(int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the number of digits to output after the decimal point.

setNumeric(boolean) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Sets if the new Attribute is to be numeric.

setNumericInfo(NumericInfo) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Sets the value of the numericInfo property.

setNumericInfo(NumericInfo) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the numericInfo property.

setNumericReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Set the numeric replacement value

setNumExamples(int) - Method in class weka.datagenerators.ClassificationGenerator

Sets the number of examples, given by option.

setNumExamples(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet

Sets the number of examples, given by option.

setNumExamples(int) - Method in class weka.datagenerators.RegressionGenerator

Sets the number of examples, given by option.

setNumExecutionSlots(int) - Method in class weka.attributeSelection.GreedyStepwise

Sets the number of threads

setNumExecutionSlots(int) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Set the number of execution slots (threads) to use for building the members of the ensemble.

setNumExecutionSlots(int) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Set the number of execution slots (threads) to use for building the members of the ensemble.

setNumExecutionSlots(int) - Method in class weka.classifiers.trees.RandomForest

Set the number of execution slots (threads) to use for building the members of the ensemble.

setNumExecutionSlots(int) - Method in class weka.clusterers.EM

Set the degree of parallelism to use.

setNumExecutionSlots(int) - Method in class weka.clusterers.SimpleKMeans

Set the degree of parallelism to use.

setNumFeatures(int) - Method in class weka.classifiers.trees.RandomForest

Set the number of features to use in random selection.

setNumFolds(int) - Method in class weka.classifiers.functions.SMO

Set the value of numFolds.

setNumFolds(int) - Method in class weka.classifiers.meta.CVParameterSelection

Sets the number of folds for the cross-validation.

setNumFolds(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Set the value of NumFolds.

setNumFolds(int) - Method in class weka.classifiers.meta.MultiScheme

Sets the number of folds for cross-validation.

setNumFolds(int) - Method in class weka.classifiers.meta.Stacking

Sets the number of folds for the cross-validation.

setNumFolds(int) - Method in class weka.classifiers.rules.PART

Set the value of numFolds.

setNumFolds(int) - Method in class weka.classifiers.trees.J48

Set the value of numFolds.

setNumFolds(int) - Method in class weka.classifiers.trees.RandomTree

Set the value of NumFolds.

setNumFolds(int) - Method in class weka.classifiers.trees.REPTree

Set the value of NumFolds.

setNumFolds(int) - Method in class weka.clusterers.EM

Set the number of folds to use when cross-validating to find the best number of clusters.

setNumFolds(int) - Method in class weka.experiment.CrossValidationResultProducer

Set the value of NumFolds.

setNumFolds(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Sets the number of folds the dataset is split into.

setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Sets the number of folds the dataset is split into.

setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the number of cross-validation folds to use - < 2 means no cross-validation.

setNumInstances(int) - Method in class weka.core.CheckScheme

Sets the number of instances to use in the datasets (some classifiers might require more instances).

setNumInstances(int) - Method in class weka.core.TestInstances

sets the number of instances to produce

setNumInstances(Random) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the real number of instances for this cluster.

setNumInstances(int) - Method in class weka.estimators.CheckEstimator

Sets the number of instances to use in the datasets (some estimators might require more instances).

setNumInstancesRelational(int) - Method in class weka.core.CheckScheme

sets the number of instances in relational/bag attributes to produce

setNumInstancesRelational(int) - Method in class weka.core.TestInstances

sets the number of instances in relational/bag attributes to produce

setNumIrrelevant(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the number of irrelevant attributes.

setNumIterations(int) - Method in class weka.classifiers.functions.VotedPerceptron

Set the value of NumIterations.

setNumIterations(int) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Sets the number of bagging iterations

setNumNeighbours(int) - Method in class weka.attributeSelection.ReliefFAttributeEval

Set the number of nearest neighbours

setNumNominal(int) - Method in class weka.core.CheckScheme

sets the number of nominal attributes

setNumNominal(int) - Method in class weka.core.TestInstances

sets the number of nominal attributes

setNumNominalValues(int) - Method in class weka.core.TestInstances

sets the number of values for nominal attributes

setNumNumeric(int) - Method in class weka.core.CheckScheme

sets the number of numeric attributes

setNumNumeric(int) - Method in class weka.core.TestInstances

sets the number of numeric attributes

setNumNumeric(int) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the number of numerical attributes.

setNumOfPredictors(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the numOfPredictors property.

setNumOfRecords(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the numOfRecords property.

setNumOfRecordsWeighted(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the numOfRecordsWeighted property.

setNumRelational(int) - Method in class weka.core.CheckScheme

sets the number of relational attributes

setNumRelational(int) - Method in class weka.core.TestInstances

sets the number of relational attributes

setNumRelationalDate(int) - Method in class weka.core.TestInstances

sets the number of date attributes in a relational attribute

setNumRelationalNominal(int) - Method in class weka.core.TestInstances

sets the number of nominal attributes in a relational attribute

setNumRelationalNominalValues(int) - Method in class weka.core.TestInstances

sets the number of values for nominal attributes in a relational attribute

setNumRelationalNumeric(int) - Method in class weka.core.TestInstances

sets the number of numeric attributes in a relational attribute

setNumRelationalString(int) - Method in class weka.core.TestInstances

sets the number of string attributes in a relational attribute

setNumRules(int) - Method in class weka.associations.Apriori

Set the value of numRules.

setNumRulesToFind(int) - Method in class weka.associations.FPGrowth

Set the desired number of rules to find.

setNumRuns(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Set the value of NumRuns.

setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the number of points to uniformly sample from a region (fixed dimensions).

setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the number of points to uniformly sample from a region (fixed dimensions).

setNumString(int) - Method in class weka.core.CheckScheme

sets the number of string attributes

setNumString(int) - Method in class weka.core.TestInstances

sets the number of string attributes

setNumThreads(int) - Method in class weka.attributeSelection.CfsSubsetEval

Sets the number of threads

setNumToSelect(int) - Method in class weka.attributeSelection.GreedyStepwise

Specify the number of attributes to select from the ranked list (if generating a ranking).

setNumToSelect(int) - Method in interface weka.attributeSelection.RankedOutputSearch

Specify the number of attributes to select from the ranked list.

setNumToSelect(int) - Method in class weka.attributeSelection.Ranker

Specify the number of attributes to select from the ranked list.

setNumTrees(int) - Method in class weka.classifiers.trees.RandomForest

Set the value of numTrees.

setNumValues(int) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Sets how many values are retained

setObject(Object) - Method in class weka.core.CheckGOE

Set the object to work on..

setObject(Object) - Method in class weka.gui.beans.AssociatorCustomizer

Set the classifier object to be edited

setObject(Object) - Method in class weka.gui.beans.AttributeSummarizerCustomizer

Set the model performance chart object to customize

setObject(Object) - Method in class weka.gui.beans.ClassAssignerCustomizer

Set the bean to be edited

setObject(Object) - Method in class weka.gui.beans.ClassifierCustomizer

Set the classifier object to be edited

setObject(Object) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer

Set the ClassifierPerformanceEvaluator to be customized

setObject(Object) - Method in class weka.gui.beans.ClassValuePickerCustomizer

Set the bean to be edited

setObject(Object) - Method in class weka.gui.beans.ClustererCustomizer

Set the Clusterer object to be edited

setObject(Object) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

Set the object to be edited

setObject(Object) - Method in class weka.gui.beans.DataVisualizerCustomizer

Set the model performance chart object to customize

setObject(Object) - Method in class weka.gui.beans.FilterCustomizer

Set the filter bean to be edited

setObject(Object) - Method in class weka.gui.beans.FlowByExpressionCustomizer

setObject(Object) - Method in class weka.gui.beans.ImageSaverCustomizer

Set the ImageSaver object to customize.

setObject(Object) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

Set the object to be edited

setObject(Object) - Method in class weka.gui.beans.JoinCustomizer

setObject(Object) - Method in class weka.gui.beans.LoaderCustomizer

Set the loader to be customized

setObject(Object) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer

Set the model performance chart object to customize

setObject(Object) - Method in class weka.gui.beans.NoteCustomizer

setObject(Object) - Method in class weka.gui.beans.PredictionAppenderCustomizer

Set the object to be edited

setObject(Object) - Method in class weka.gui.beans.SaverCustomizer

Set the saver to be customized

setObject(Object) - Method in class weka.gui.beans.SerializedModelSaverCustomizer

Set the model saver to be customized

setObject(Object) - Method in class weka.gui.beans.SorterCustomizer

Set the object to edit

setObject(Object) - Method in class weka.gui.beans.StripChartCustomizer

Set the StripChart object to be customized

setObject(Object) - Method in class weka.gui.beans.SubstringLabelerCustomizer

Set the SubstringLabeler to edit

setObject(Object) - Method in class weka.gui.beans.SubstringReplacerCustomizer

Set the SubstringReplacer to edit

setObject(Object) - Method in class weka.gui.beans.TextSaverCustomizer

Set the TextSaver object to customize.

setObject(Object) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer

Set the TrainTestSplitMaker to be customized

setObject(Object) - Method in class weka.gui.filters.AddUserFieldsCustomizer

Set the filter to edit.

setOccurrence(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the occurrence property.

setOccurrence(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the occurrence property.

setOffDiagDefault(Double) - Method in class weka.core.pmml.jaxbbindings.Matrix

Sets the value of the offDiagDefault property.

setOffDiskReportingFrequency(int) - Method in class weka.associations.FPGrowth

Set how often to report some progress when the data is being read incrementally off of the disk rather than loaded into memory.

setOffscreenAdditionalOpts(String) - Method in class weka.gui.beans.DataVisualizer

Set the additional options for the offscreen renderer

setOffscreenAdditionalOpts(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the additional options for the offscreen renderer

setOffscreenHeight(String) - Method in class weka.gui.beans.DataVisualizer

Set the height (in pixels) of the offscreen image to generate

setOffscreenHeight(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the height (in pixels) of the offscreen image to generate

setOffscreenRendererName(String) - Method in class weka.gui.beans.DataVisualizer

Set the name of the renderer to use for offscreen chart rendering operations

setOffscreenRendererName(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the name of the renderer to use for offscreen chart rendering operations

setOffscreenWidth(String) - Method in class weka.gui.beans.DataVisualizer

Set the width (in pixels) of the offscreen image to generate.

setOffscreenWidth(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the width (in pixels) of the offscreen image to generate.

setOffscreenXAxis(String) - Method in class weka.gui.beans.DataVisualizer

Set the name of the attribute for the x-axis in offscreen plots.

setOffscreenXAxis(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the name of the attribute for the x-axis in offscreen plots.

setOffscreenYAxis(String) - Method in class weka.gui.beans.DataVisualizer

Set the name of the attribute for the y-axis in offscreen plots.

setOffscreenYAxis(String) - Method in class weka.gui.beans.ModelPerformanceChart

Set the name of the attribute for the y-axis in offscreen plots.

setOffset(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Sets the value of the offset property.

setOffsetValue(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the offsetValue property.

setOffsetVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the offsetVariable property.

setOkButtonText(String) - Method in class weka.gui.GenericObjectEditor.GOEPanel

Allows customization of the action label on the dialog.

setOmega(double) - Method in class weka.classifiers.functions.supportVector.Puk

Sets the omega value.

setOn(boolean) - Method in class weka.gui.visualize.ClassPanel

Enables the panel

setOnDemandDirectory(File) - Method in class weka.classifiers.meta.CostSensitiveClassifier

Sets the directory that will be searched for cost files when loading on demand.

setOnDemandDirectory(File) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Sets the directory that will be searched for cost files when loading on demand.

setOperator(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate

Sets the value of the operator property.

setOperator(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Sets the value of the operator property.

setOptimalColumnWidth(int) - Method in class weka.gui.JTableHelper

sets the optimal column width for the given column

setOptimalColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper

sets the optimal column width for the given column

setOptimalColumnWidth() - Method in class weka.gui.JTableHelper

sets the optimal column width for all columns

setOptimalColumnWidth(JTable) - Static method in class weka.gui.JTableHelper

sets the optimal column width for alls column if the given table

setOptimalColWidth() - Method in class weka.gui.arffviewer.ArffPanel

calculates the optimal column width for the current column

setOptimalColWidths() - Method in class weka.gui.arffviewer.ArffPanel

calculates the optimal column widths for all columns

setOptimalColWidths() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

sets the optimal column width for all columns

setOptimalHeaderWidth(int) - Method in class weka.gui.JTableHelper

sets the optimal header width for the given column

setOptimalHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper

sets the optimal header width for the given column

setOptimalHeaderWidth() - Method in class weka.gui.JTableHelper

sets the optimal header width for all columns

setOptimalHeaderWidth(JTable) - Static method in class weka.gui.JTableHelper

sets the optimal header width for alls column if the given table

setOptimizations(int) - Method in class weka.classifiers.rules.JRip

Sets the number of optimization runs

setOptimumLiftGraph(OptimumLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the optimumLiftGraph property.

setOptionHandler(OptionHandler) - Method in class weka.core.CheckOptionHandler

Set the OptionHandler to work on..

setOptions(String[]) - Method in class weka.associations.Apriori

Parses a given list of options.

setOptions(String[]) - Method in class weka.associations.CheckAssociator

Parses a given list of options.

setOptions(String[]) - Method in class weka.associations.FilteredAssociator

Parses a given list of options.

setOptions(String[]) - Method in class weka.associations.FPGrowth

Parses a given list of options.

setOptions(String[]) - Method in class weka.associations.SingleAssociatorEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.BestFirst

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.CfsSubsetEval

Parses and sets a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.CheckAttributeSelection

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.CorrelationAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.GainRatioAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.GreedyStepwise

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.InfoGainAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.OneRAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.PrincipalComponents

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.Ranker

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.ReliefFAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.attributeSelection.WrapperSubsetEval

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.AbstractClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.BayesNet

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.NaiveBayes

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.BayesNetGenerator

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.HillClimber

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.K2

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TAN

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.HillClimber

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.K2

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TAN

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.BVDecompose

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.CheckClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.CheckSource

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.evaluation.output.prediction.CSV

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcesses

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.LinearRegression

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.Logistic

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.MultilayerPerceptron

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SGD

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SGDText

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLinearRegression

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLogistic

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SMO

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.SMOreg

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.CachedKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.CheckKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.Kernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.PolyKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.Puk

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RBFKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegSMO

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.StringKernel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.VotedPerceptron

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.lazy.IBk

Parses a given list of options.

setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute

Sets the options.

setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Set options.

setOptions(String[]) - Method in class weka.classifiers.lazy.KStar

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.lazy.LWL

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AdaBoostM1

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AdditiveRegression

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.Bagging

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.CostSensitiveClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.CVParameterSelection

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.FilteredClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.LogitBoost

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.MultiClassClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.MultiScheme

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.RandomSubSpace

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.RegressionByDiscretization

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.Stacking

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.Vote

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.misc.InputMappedClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.misc.SerializedClassifier

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.MultipleClassifiersCombiner

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableClassifier

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.rules.DecisionTable

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.rules.JRip

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.rules.OneR

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.rules.PART

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.SingleClassifierEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.HoeffdingTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.J48

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.LMT

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.m5.M5Base

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.M5P

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.RandomForest

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.RandomTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.REPTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.AbstractClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.Canopy

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.CheckClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.Cobweb

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.EM

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.FarthestFirst

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.FilteredClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.HierarchicalClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.MakeDensityBasedClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.RandomizableClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.SimpleKMeans

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.SingleClustererEnhancer

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.Check

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.CheckGOE

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.CheckOptionHandler

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.CheckScheme

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.converters.AbstractFileSaver

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.converters.ArffSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.C45Saver

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.converters.CSVLoader

setOptions(String[]) - Method in class weka.core.converters.CSVSaver

Valid options are:

setOptions(String[]) - Method in class weka.core.converters.DatabaseLoader

Sets the options.

setOptions(String[]) - Method in class weka.core.converters.DatabaseSaver

Sets the options.

setOptions(String[]) - Method in class weka.core.converters.JSONSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.LibSVMSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.MatlabSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.SVMLightSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.TextDirectoryLoader

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.converters.XRFFSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.FindWithCapabilities

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.Javadoc

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.ListOptions

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.MinkowskiDistance

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.BallTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.CoverTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.KDTree

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.LinearNNSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.NearestNeighbourSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.NormalizableDistance

Parses a given list of options.

setOptions(String[]) - Method in interface weka.core.OptionHandler

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.OptionHandlerJavadoc

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.stemmers.SnowballStemmer

Parses the options.

setOptions(String[]) - Method in class weka.core.TechnicalInformationHandlerJavadoc

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.TestInstances

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.tokenizers.NGramTokenizer

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.tokenizers.Tokenizer

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.datagenerators.ClassificationGenerator

Sets the options.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.Agrawal

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.BayesNet

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.LED24

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.RandomRBF

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.RDG1

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.regression.Expression

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.classifiers.regression.MexicanHat

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.ClusterDefinition

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.clusterers.SubspaceCluster

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.ClusterGenerator

Sets the options.

setOptions(String[]) - Method in class weka.datagenerators.DataGenerator

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.datagenerators.RegressionGenerator

Sets the options.

setOptions(String[]) - Method in class weka.estimators.CheckEstimator

Parses a given list of options.

setOptions(String[]) - Method in class weka.estimators.Estimator

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.AveragingResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.CrossValidationResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.CSVResultListener

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.DatabaseResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.Experiment

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.ExplicitTestsetResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.InstanceQuery

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.LearningRateResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.PairedTTester

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.RandomSplitResultProducer

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.RegressionSplitEvaluator

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.ResultMatrix

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.CheckSource

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.MultiFilter

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.SimpleFilter

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.AddClassification

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.AttributeSelection

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.ClassOrder

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.Discretize

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.NominalToBinary

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.PartitionMembership

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.instance.Resample

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.instance.SpreadSubsample

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Parses a given list of options controlling the behaviour of this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Add

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddCluster

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddExpression

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddID

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddNoise

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddUserFields

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ClassAssigner

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ClusterMembership

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Copy

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Discretize

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MathExpression

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeManyValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToString

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Normalize

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericCleaner

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericToNominal

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RandomSubset

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Remove

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveByName

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveType

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveUseless

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Reorder

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SortLabels

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToNominal

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SwapValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Randomize

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemovePercentage

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveRange

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Resample

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.ReservoirSample

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SubsetByExpression

Parses a given list of options.

setOptions(String[]) - Method in class weka.gui.explorer.AbstractPlotInstances

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.gui.Main

Parses the options for this object.

setOptions(String[]) - Method in class weka.gui.scripting.Script

Parses a given list of options.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DefineFunction

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DerivedField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.ParameterField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the optype property.

setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the optype property.

setOrder(double) - Method in class weka.core.MinkowskiDistance

Sets the order.

setOrig(double) - Method in class weka.core.pmml.jaxbbindings.LinearNorm

Sets the value of the orig property.

setOriginalCoords(Vector<Point>) - Method in class weka.gui.beans.MetaBean

sets the vector containing the original coordinates (instances of class Point) for the inputs

setOutlierFactor(double) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Sets the factor for determining the thresholds for outliers.

setOutliers(OUTLIERTREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the outliers property.

setOutliers(OUTLIERTREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.NormContinuous

Sets the value of the outliers property.

setOutput(Output) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the output property.

setOutput(Output) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the output property.

setOutput(PrintWriter) - Method in class weka.datagenerators.DataGenerator

Sets the print writer.

setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.LinearRegression

Set whether to output additional statistics (such as std.

setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegression

Set whether to output additional statistics (such as std.

setOutputClassification(boolean) - Method in class weka.filters.supervised.attribute.AddClassification

Set whether the classification of the classifier is output.

setOutputColumn(String) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the outputColumn property.

setOutputDetailedInfo(boolean) - Method in class weka.attributeSelection.CorrelationAttributeEval

Set whether to output per-value correlation for nominal attributes

setOutputDistribution(boolean) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets whether to output the class distribution or not.

setOutputDistribution(boolean) - Method in class weka.filters.supervised.attribute.AddClassification

Set whether the Distribution of the classifier is output.

setOutputErrorFlag(boolean) - Method in class weka.filters.supervised.attribute.AddClassification

Set whether the classification of the classifier is output.

setOutputFile(File) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets the output file to write to.

setOutputFile(File) - Method in class weka.experiment.CrossValidationResultProducer

Set the value of OutputFile.

setOutputFile(File) - Method in class weka.experiment.CSVResultListener

Set the value of OutputFile.

setOutputFile(File) - Method in class weka.experiment.ExplicitTestsetResultProducer

Set the value of OutputFile.

setOutputFile(File) - Method in class weka.experiment.RandomSplitResultProducer

Set the value of OutputFile.

setOutputFilename(boolean) - Method in class weka.core.converters.TextDirectoryLoader

Sets whether the filename will be stored as an extra attribute.

setOutputFileName(String) - Method in class weka.experiment.CSVResultListener

Set the value of OutputFileName.

setOutputFilename(String) - Method in class weka.gui.GenericPropertiesCreator

sets the file to output the properties for the GEO to

setOutputFormat(int) - Method in class weka.core.Debug.Clock

sets the format of the output

setOutputFormatFromDialog() - Method in class weka.gui.experiment.ResultsPanel

displays the Dialog for the output format and sets the chosen settings, if the user approves.

setOutputItemSets(boolean) - Method in class weka.associations.Apriori

Sets whether itemsets are output as well

setOutputNeuron(String) - Method in class weka.core.pmml.jaxbbindings.NeuralOutput

Sets the value of the outputNeuron property.

setOutputOffsetMultiplier(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange

Set whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.

setOutputPerClassInfoRetrievalStats(boolean) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Set whether to output per-class information retrieval statistics (nominal class only).

setOutputProbsForSVM(boolean) - Method in class weka.classifiers.functions.SGDText

Set whether to fit a logistic regression (itself trained using SGD) to the outputs of the SVM (if an SVM is being learned).

setOutputs(Vector<Object>) - Method in class weka.gui.beans.MetaBean

setOutputTypes(String) - Method in class weka.core.Debug.DBO

Switches the outputs on that are requested from the option O

setOutputWordCounts(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether output instances contain 0 or 1 indicating word presence, or word counts.

setOverwriteWarning(boolean) - Method in class weka.gui.ConverterFileChooser

Whether a warning is popped up if the file that is to be saved already exists (only save dialog).

setOwner(CapabilitiesHandler) - Method in class weka.core.Capabilities

sets the owner of this capabilities object

setP(double) - Method in class weka.classifiers.BVDecomposeSegCVSub

Set the proportion of instances that are common between two training sets used to train a classifier.

setPaint(Paint) - Method in class weka.gui.visualize.PostscriptGraphics

setPaintMode() - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

setPanelHeight(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the height of the visualization

setPanelWidth(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the width of the visualization

setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInArithmetic

Set the structure of the parameters that are expected as input by this function.

setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInMath

Set the structure of the parameters that are expected as input by this function.

setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInString

Set the structure of the parameters that are expected as input by this function.

setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.DefineFunction

Set the structure of the parameters that are expected as input by this function.

setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Function

Set the structure of the parameters that are expected as input by this function.

setParameterName(String) - Method in class weka.core.pmml.jaxbbindings.PCell

Sets the value of the parameterName property.

setParameterName(String) - Method in class weka.core.pmml.jaxbbindings.PPCell

Sets the value of the parameterName property.

SetParent(int, int) - Method in class weka.classifiers.bayes.net.ParentSet

sets index parent of parent specified by index

setParent(ClusterGenerator) - Method in class weka.datagenerators.ClusterDefinition

sets the parent datagenerator this cluster belongs to

setParent(SubspaceCluster) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

sets the parent datagenerator this cluster belongs to

setParent(Container) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

sets the new parent frame

setParent(Edge) - Method in class weka.gui.treevisualizer.Node

Set the value of parent.

setParentField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the parentField property.

setParentFrame(JFrame) - Method in class weka.gui.SetInstancesPanel

Sets the frame, this panel resides in.

setParentLevelField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the parentLevelField property.

setParentSeparator(MarginCalculator.JunctionTreeSeparator) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

setParentWindow(Window) - Method in class weka.gui.beans.AssociatorCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.AttributeSummarizerCustomizer

Set the parent window of this dialog

setParentWindow(Window) - Method in class weka.gui.beans.ClassAssignerCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ClassifierCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ClassValuePickerCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ClustererCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

setParentWindow(Window) - Method in interface weka.gui.beans.CustomizerCloseRequester

A reference to the parent is passed in

setParentWindow(Window) - Method in class weka.gui.beans.DataVisualizerCustomizer

Set the parent window of this dialog

setParentWindow(Window) - Method in class weka.gui.beans.FilterCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.FlowByExpressionCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ImageSaverCustomizer

Set the parent window of this dialog

setParentWindow(Window) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.JoinCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.LoaderCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer

Set the parent window of this dialog

setParentWindow(Window) - Method in class weka.gui.beans.NoteCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.PredictionAppenderCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.SaverCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.SerializedModelSaverCustomizer

setParentWindow(Window) - Method in class weka.gui.beans.SorterCustomizer

Set the parent window for this dialog

setParentWindow(Window) - Method in class weka.gui.beans.SubstringLabelerCustomizer

Set a reference to the parent window/dialog containing this panel

setParentWindow(Window) - Method in class weka.gui.beans.SubstringReplacerCustomizer

Set a reference to the parent window/dialog containing this panel

setParentWindow(Window) - Method in class weka.gui.beans.TextSaverCustomizer

Set the parent window of this dialog

setPartialScore(Double) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the partialScore property.

setPartition(Partition) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the partition property.

setPartition(Partition) - Method in class weka.core.pmml.jaxbbindings.TargetValue

Sets the value of the partition property.

setPartitionGenerator(PartitionGenerator) - Method in class weka.filters.supervised.attribute.PartitionMembership

Set the generator for use in filtering

setPassword(String) - Method in interface weka.core.converters.DatabaseConverter

setPassword(String) - Method in class weka.core.converters.DatabaseLoader

Sets user password for the database

setPassword(String) - Method in class weka.core.converters.DatabaseSaver

Sets the database password.

setPassword(String) - Method in class weka.experiment.DatabaseUtils

Set the database password.

setPassword(String) - Method in class weka.gui.sql.ConnectionPanel

sets the Password.

setPasteBuffer(StringBuffer) - Method in class weka.gui.beans.KnowledgeFlowApp

Set the contents of the "paste" buffer and enable the paste from cliboard toolbar button

setPattern(SelectedTag) - Method in class weka.datagenerators.clusterers.BIRCHCluster

Sets the pattern type.

setPCol(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the pCol property.

setPercent(int) - Method in class weka.filters.unsupervised.attribute.AddNoise

Sets the size of noise data, as a percentage of the original set.

setPercent(double) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets the percent the attributes (dimensions) of the data should be reduced to

setPercent() - Method in class weka.gui.visualize.MatrixPanel

Calculates the percentage to resample

setPercentage(double) - Method in class weka.filters.unsupervised.instance.RemovePercentage

Sets the percentage of intances to select.

setPercentCompleted(int) - Method in class weka.gui.boundaryvisualizer.RemoteResult

Set the progress for this row so far

setPeriod(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the period property.

setPeriodicPruning(int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set how often to prune the dictionary

setPeriodicPruning(int) - Method in class weka.classifiers.functions.SGDText

Set how often to prune the dictionary

setPeriodicPruning(double) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.

setPeriodicPruningRate(int) - Method in class weka.clusterers.Canopy

Set the how often to prune low density canopies during training

setPerturbationFraction(double) - Method in class weka.datagenerators.classifiers.classification.Agrawal

Sets the perturbation fraction.

setPhase(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the phase property.

setPhi(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Sets the value of the phi property.

setPivot(Instance) - Method in class weka.core.neighboursearch.balltrees.BallNode

Sets the pivot/centre of this nodes ball.

setPixHeight(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the height of a pixel

setPixWidth(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the width of a pixel

setPlotCompanion(Plot2DCompanion) - Method in class weka.gui.visualize.Plot2D

Set a companion class.

setPlotList(ArrayList<PlotData2D>) - Method in class weka.gui.visualize.LegendPanel

Set the list of plots to generate legend entries for

setPlotName(String) - Method in class weka.gui.visualize.PlotData2D

Set the name of this plot

setPlotNameHTML(String) - Method in class weka.gui.visualize.PlotData2D

Set the plot name for use in a tool tip text.

setPlotShapes(ArrayList<Integer>) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Set the vector of plot shapes to use;

setPlotSizes(ArrayList<Object>) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Set the vector of plot sizes to use

setPlotTrainingData(boolean) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set whether to superimpose the training data plot

setPlus(int, double) - Method in class weka.core.matrix.DoubleVector

Adds a value to an element

setPMMLVersion(Document) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier

Set the version of PMML used for this model.

setPMMLVersion(Document) - Method in interface weka.core.pmml.PMMLModel

Set the version of the PMML.

setPoints(MiddleOutConstructor.TempNode, int, int, int[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the points of an anchor node.

setPointSizeProportionalToMargin(boolean) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Set whether the point size should be proportional to the prediction margin (classification only).

setPoissonDistribution(PoissonDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate

Sets the value of the poissonDistribution property.

setPoissonDistribution(PoissonDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the poissonDistribution property.

setPoolSize(int) - Method in class weka.attributeSelection.CfsSubsetEval

Sets the number of threads

setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

setPopup(JPopupMenu) - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

sets the JPopupMenu to display again after closing the dialog.

setPosition(int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet

set position of node

setPosition(int, int, int, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet

Set position of node.

setPositiveIndex(int) - Method in class weka.associations.FPGrowth

Set the index of the attribute value to consider as positive for binary attributes in normal dense instances.

setPositiveTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC

Sets the value of the positiveTargetFieldDisplayValue property.

setPositiveTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC

Sets the value of the positiveTargetFieldValue property.

setPostProcessor(CheckScheme.PostProcessor) - Method in class weka.core.CheckScheme

sets the PostProcessor to use

setPostProcessor(CheckEstimator.PostProcessor) - Method in class weka.estimators.CheckEstimator

sets the PostProcessor to use

setPParameter(double) - Method in class weka.core.pmml.jaxbbindings.Minkowski

Sets the value of the pParameter property.

setPreBuiltClassifiers(File[]) - Method in class weka.classifiers.meta.Vote

Set the paths to pre-built serialized classifiers to load and include in the ensemble

setPrecision(Double) - Method in class weka.core.pmml.jaxbbindings.VerificationField

Sets the value of the precision property.

setPreComputeCorrelationMatrix(boolean) - Method in class weka.attributeSelection.CfsSubsetEval

Set whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.

SetPredicate - Class in weka.core.pmml.jaxbbindings

Java class for SetPredicate element declaration.

SetPredicate() - Constructor for class weka.core.pmml.jaxbbindings.SetPredicate

setPredictionIntervals(double[][]) - Method in class weka.classifiers.evaluation.NumericPrediction

Sets the prediction intervals for this prediction.

setPredictorName(String) - Method in class weka.core.pmml.jaxbbindings.PPCell

Sets the value of the predictorName property.

setPredTargetColumn(boolean) - Method in class weka.experiment.ClassifierSplitEvaluator

Set the flag for prediction and target output.

setPreferredScrollableViewportSize(Dimension) - Method in class weka.gui.AttributeSelectionPanel

setPrefix(String) - Method in class weka.gui.beans.SerializedModelSaver

Set the prefix to prepend to the model file names.

setPreprocessing(Filter) - Method in class weka.filters.unsupervised.attribute.KernelFilter

Sets the filter to use for preprocessing (use the AllFilter for no preprocessing)

setPreserveInstancesOrder(boolean) - Method in class weka.clusterers.SimpleKMeans

Sets whether order of instances must be preserved.

setPreserveOrder(boolean) - Method in class weka.gui.beans.CrossValidationFoldMaker

Sets whether the order of the incoming instances is to be preserved under cross-validation (no randomization or stratification is done in this case).

setPrintColNames(boolean) - Method in class weka.experiment.ResultMatrix

sets whether the column names or numbers instead are printed.

setPrintLeafModels(boolean) - Method in class weka.classifiers.trees.HoeffdingTree

setPrintNewick(boolean) - Method in class weka.clusterers.HierarchicalClusterer

setPrintRowNames(boolean) - Method in class weka.experiment.ResultMatrix

sets whether the row names or numbers instead are printed deactivating automatically sets m_EnumerateColNames to TRUE.

setPrintTrees(boolean) - Method in class weka.classifiers.trees.RandomForest

Set whether to print the individual ensemble trees in the output

setPriorProbability(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.TargetValue

Sets the value of the priorProbability property.

setPriors(Instances) - Method in class weka.classifiers.evaluation.Evaluation

Sets the class prior probabilities.

setPriors(Instances) - Method in class weka.classifiers.Evaluation

Sets the class prior probabilities.

setProbability(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Sets the value of the probability property.

setProducer(String) - Method in class weka.associations.AssociationRules

Set a textual description of the scheme that produced these rules.

setProlog(boolean) - Method in class weka.core.OptionHandlerJavadoc

sets whether to add the "Valid options are..." prolog

setProlog(boolean) - Method in class weka.core.TechnicalInformationHandlerJavadoc

sets whether to add the "Valid options are..." prolog

setProperty(String) - Method in class weka.core.pmml.jaxbbindings.Value

Sets the value of the property property.

setProperty(String, String) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

setPropertyArray(Object) - Method in class weka.experiment.Experiment

Sets the array of values to set the custom property to.

setPropertyArray(Object) - Method in class weka.experiment.RemoteExperiment

Sets the array of values to set the custom property to.

setPropertyPath(PropertyNode[]) - Method in class weka.experiment.Experiment

Sets the path of properties taken to get to the custom property to iterate over.

setPropertyPath(PropertyNode[]) - Method in class weka.experiment.RemoteExperiment

Sets the path of properties taken to get to the custom property to iterate over.

setPRow(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the pRow property.

setPruningMethod(SelectedTag) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets the method used to for pruning.

setPValue(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the pValue property.

setPValueAlpha(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the pValueAlpha property.

setPValueFinal(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the pValueFinal property.

setPValueInitial(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the pValueInitial property.

setQuality(float) - Method in class weka.gui.visualize.JPEGWriter

sets the quality the JPEG is saved in.

setQuantileLimit(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.Quantile

Sets the value of the quantileLimit property.

setQuantileValue(double) - Method in class weka.core.pmml.jaxbbindings.Quantile

Sets the value of the quantileValue property.

setQuery(String) - Method in class weka.core.converters.DatabaseLoader

Sets the query to execute against the database

setQuery(String) - Method in class weka.experiment.InstanceQuery

Set the query to execute against the database

setQuery(String) - Method in class weka.gui.sql.QueryPanel

sets the query in the textarea.

setQueryPanel(QueryPanel) - Method in class weka.gui.sql.ResultPanel

sets the QueryPanel to use for displaying the query

setQuoteDelimiters(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the quote delimiter characters to use.

setQuoteEscape(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the character to use for escaping a quote character.

setRadius(double) - Method in class weka.core.neighboursearch.balltrees.BallNode

Sets the radius of the node's ball.

setRandom(Random) - Method in class weka.datagenerators.DataGenerator

Sets the random generator.

setRandomizeData(boolean) - Method in class weka.experiment.ExplicitTestsetResultProducer

Set to true if dataset is to be randomized.

setRandomizeData(boolean) - Method in class weka.experiment.RandomSplitResultProducer

Set to true if dataset is to be randomized

setRandomLiftGraph(RandomLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the randomLiftGraph property.

setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2

Set random order flag

setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2

Set random order flag

setRandomSeed(int) - Method in class weka.classifiers.functions.SMO

Set the value of randomSeed.

setRandomSeed(int) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Sets the seed for random number generator.

setRandomSeed(int) - Method in class weka.filters.supervised.instance.Resample

Sets the random number seed.

setRandomSeed(int) - Method in class weka.filters.supervised.instance.SpreadSubsample

Sets the random number seed.

setRandomSeed(int) - Method in class weka.filters.unsupervised.attribute.AddNoise

Sets the random number seed.

setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Randomize

Set the random number generator seed value.

setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Resample

Sets the random number seed.

setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.ReservoirSample

Sets the random number seed.

setRandomWidthFactor(double) - Method in class weka.classifiers.meta.MultiClassClassifier

Sets the multiplier when generating random codes.

setRange(String) - Method in class weka.core.InstanceComparator

Sets the attribute range to use for comparison.

setRanges(String) - Method in class weka.core.Range

Sets the ranges from a string representation.

setRanges(Range[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Sets the list of possible Ranges to choose from.

setRank(BigInteger) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the rank property.

setRankBasis(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the rankBasis property.

setRanking(boolean) - Method in class weka.attributeSelection.AttributeSelection

produce a ranking (if possible with the set search and evaluator)

setRanking(int[][]) - Method in class weka.experiment.ResultMatrix

sets the ranking data based on the wins.

setRankingQuality(Double) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the rankingQuality property.

setRankOrder(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the rankOrder property.

setRawOutput(boolean) - Method in class weka.experiment.CrossValidationResultProducer

Set to true if raw split evaluator output is to be saved

setRawOutput(boolean) - Method in class weka.experiment.ExplicitTestsetResultProducer

Set to true if raw split evaluator output is to be saved.

setRawOutput(boolean) - Method in class weka.experiment.RandomSplitResultProducer

Set to true if raw split evaluator output is to be saved

setReadable(String) - Method in class weka.core.Tag

Sets the string description of the Tag.

setReadIncrementally(boolean) - Method in class weka.gui.SetInstancesPanel

Sets whether or not instances should be read incrementally by the Loader.

setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffPanel

sets whether the model is read-only

setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel

sets whether the model is read-only

setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffTable

sets whether the model is read-only

setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffTableModel

sets whether the model is read-only

setREALSparseArray(REALSparseArray) - Method in class weka.core.pmml.jaxbbindings.VectorInstance

Sets the value of the realSparseArray property.

setReasonCode(String) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the reasonCode property.

setReasonCode(String) - Method in class weka.core.pmml.jaxbbindings.Characteristic

Sets the value of the reasonCode property.

setReasonCodeAlgorithm(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the reasonCodeAlgorithm property.

setRecordCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Sets the value of the recordCount property.

setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.Node

Sets the value of the recordCount property.

setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet

Sets the value of the recordCount property.

setRecordCount(double) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Sets the value of the recordCount property.

setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the recordCount property.

setRecordCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the recordCount property.

setReducedErrorPruning(boolean) - Method in class weka.classifiers.rules.PART

Set the value of reducedErrorPruning.

setReducedErrorPruning(boolean) - Method in class weka.classifiers.trees.J48

Set the value of reducedErrorPruning.

setReduceNumberOfDistanceCalcsViaCanopies(boolean) - Method in class weka.clusterers.SimpleKMeans

Set whether to use canopies to reduce the number of distance computations required

setRefer(String) - Method in class weka.gui.treevisualizer.Node

Set the value of refer.

SetReference - Class in weka.core.pmml.jaxbbindings

Java class for SetReference element declaration.

SetReference() - Constructor for class weka.core.pmml.jaxbbindings.SetReference

setReferencePoint(Double) - Method in class weka.core.pmml.jaxbbindings.Parameter

Sets the value of the referencePoint property.

setRefreshFreq(int) - Method in class weka.gui.beans.StripChart

Set how often (in x axis points) to refresh the display

setRegex(boolean) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Set whether this is a regular expression match or not

setRegex(boolean) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Set whether this is a regular expression match or not

setRegOptimizer(RegOptimizer) - Method in class weka.classifiers.functions.SMOreg

sets the learning algorithm

setRegressionModel(RegressionModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the regressionModel property.

setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.Rule

Set the value of regressionTree.

setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.RuleNode

Set the value of regressionTree.

setRelation(String) - Method in class weka.core.TestInstances

sets the name of the relation

setRelationalClassFormat(Instances) - Method in class weka.core.TestInstances

sets the structure for the relational class attribute

setRelationalFormat(int, Instances) - Method in class weka.core.TestInstances

sets the structure for the bags for the relational attribute

setRelationFind(String) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the regular expression to use on the relation name.

setRelationForTableName(boolean) - Method in class weka.core.converters.DatabaseSaver

En/Dis-ables that the relation name is used for the name of the table (default enabled).

setRelationName(String) - Method in class weka.core.Instances

Sets the relation's name.

setRelationName(String) - Method in class weka.datagenerators.DataGenerator

Sets the relation name the dataset should have.

setRelationNameForFilename(boolean) - Method in class weka.gui.beans.Saver

Set whether to use the relation name as the primary part of the filename.

setRelationReplace(String) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the replacement string to use on the relation name.

setRemoteHosts(DefaultListModel) - Method in class weka.experiment.RemoteExperiment

Set the list of remote host names

setRemoteHosts(Vector<String>) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed

Set a list of host names of machines to distribute processing to

setRemoveAllMissingCols(boolean) - Method in class weka.associations.Apriori

Remove columns containing all missing values.

setRemoveClassColumn(boolean) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator

Set whether the class column should be removed from the data.

setRemoveFilterName(boolean) - Method in class weka.experiment.ResultMatrix

sets whether to remove the filter classname from the dataset name.

setRemoveOldClass(boolean) - Method in class weka.filters.supervised.attribute.AddClassification

Set whether the old class attribute is removed.

setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter

Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

setRenderingHint(RenderingHints.Key, Object) - Method in class weka.gui.visualize.PostscriptGraphics

setRenderingHints(Map<?, ?>) - Method in class weka.gui.visualize.PostscriptGraphics

setReplace(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Sets the regular expression to replace matching attribute names with.

setReplace(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Set the replace string

setReplaceAll(boolean) - Method in class weka.filters.unsupervised.attribute.RenameAttribute

Sets whether to replace all occurrences or just the first one.

setReplaceMissingValues(boolean) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets either to use replace missing values filter or not

setRepresentCopiesUsingWeights(boolean) - Method in class weka.classifiers.meta.Bagging

Set whether copies of instances are represented using weights rather than explicitly.

setRescaleConstant(Double) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the rescaleConstant property.

setRescaleFactor(Double) - Method in class weka.core.pmml.jaxbbindings.Target

Sets the value of the rescaleFactor property.

setReset(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron

This sets the network up to be able to reset itself with the current settings and the learning rate at half of what it is currently.

setReset(boolean) - Method in class weka.gui.beans.ChartEvent

Set the reset flag

setResetIncrementalClassifier(boolean) - Method in class weka.gui.beans.Classifier

Set whether to reset (by calling buildClassifier()) an incremental classifier, and thus discarding any previously learned model, before processing the first instance in the incoming stream.

setResetValue(Double) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the resetValue property.

setResult(Double) - Method in class weka.core.mathematicalexpression.Parser

Sets the result of the evaluation.

setResult(Boolean) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Sets the result of the evaluation.

setResultKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel

setResultListener(ResultListener) - Method in class weka.experiment.AveragingResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.CrossValidationResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.DatabaseResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.Experiment

Sets the result listener where results will be sent.

setResultListener(ResultListener) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.LearningRateResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.RandomSplitResultProducer

Sets the object to send results of each run to.

setResultListener(ResultListener) - Method in class weka.experiment.RemoteExperiment

Sets the result listener where results will be sent.

setResultListener(ResultListener) - Method in interface weka.experiment.ResultProducer

Sets the object to send results of each run to.

setResultMatrix(ResultMatrix) - Method in class weka.experiment.PairedTTester

Sets the matrix to use to produce the output.

setResultMatrix(ResultMatrix) - Method in interface weka.experiment.Tester

Sets the matrix to use to produce the output.

setResultMatrix(ResultMatrix) - Method in class weka.gui.experiment.OutputFormatDialog

Sets the matrix to use as initial selected output format.

setResultProducer(ResultProducer) - Method in class weka.experiment.AveragingResultProducer

Set the ResultProducer.

setResultProducer(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer

Set the ResultProducer.

setResultProducer(ResultProducer) - Method in class weka.experiment.Experiment

Set the result producer used for the current experiment.

setResultProducer(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer

Set the ResultProducer.

setResultProducer(ResultProducer) - Method in class weka.experiment.RemoteExperiment

Set the result producer used for the current experiment.

setResultsetKeyColumns(Range) - Method in class weka.experiment.PairedTTester

Set the value of ResultsetKeyColumns.

setResultsetKeyColumns(Range) - Method in interface weka.experiment.Tester

Set the value of ResultsetKeyColumns.

setResultsPanel(ResultsPanel) - Method in class weka.gui.experiment.RunPanel

Sets the pointer to the results panel.

setRetrieval(int) - Method in class weka.core.converters.AbstractLoader

Sets the retrieval mode.

setRetrieval(int) - Method in class weka.core.converters.AbstractSaver

Sets the retrieval mode.

setRetrieval(int) - Method in interface weka.core.converters.Loader

Sets the retrieval mode.

setRetrieval(int) - Method in interface weka.core.converters.Saver

Sets the retrieval mode

setRidge(double) - Method in class weka.classifiers.functions.LinearRegression

Set the value of Ridge.

setRidge(double) - Method in class weka.classifiers.functions.Logistic

Sets the ridge in the log-likelihood.

setRightMargin(Double) - Method in class weka.core.pmml.jaxbbindings.Interval

Sets the value of the rightMargin property.

setRMSE(Double) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Sets the value of the rmse property.

setROC(ROC) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the roc property.

setROCGraph(ROCGraph) - Method in class weka.core.pmml.jaxbbindings.ROC

Sets the value of the rocGraph property.

setROCString(String) - Method in class weka.gui.visualize.ThresholdVisualizePanel

Set the string with ROC area

setRoot(boolean) - Method in class weka.gui.treevisualizer.Node

Set the value of root.

setRootMeanSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the rootMeanSquaredError property.

setRootNode(String) - Method in class weka.core.xml.XMLDocument

sets the root node to use in the XML output.

setRow(int, double[]) - Method in class weka.core.Matrix

Deprecated. Sets a row of the matrix to the given row.

setRow(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MatCell

Sets the value of the row property.

setRowHidden(int, boolean) - Method in class weka.experiment.ResultMatrix

sets the hidden status of the row (if the index is valid).

setRowName(int, String) - Method in class weka.experiment.ResultMatrix

sets the name of the row (if the index is valid).

setRowNameWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the row names (0 = optimal).

setRowNumber(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the row number for this sub task

setRowOrder(int[]) - Method in class weka.experiment.ResultMatrix

sets the ordering of the rows, null means default.

setRsource(String) - Method in class weka.gui.treevisualizer.Edge

Set the value of rsource.

setRSquared(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the rSquared property.

setRtarget(String) - Method in class weka.gui.treevisualizer.Edge

Set the value of rtarget.

setRuleFeature(RULEFEATURE) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the ruleFeature property.

setRules(List<AssociationRule>) - Method in class weka.associations.AssociationRules

Set the rules to use.

setRules(List<AssociationRule>) - Method in class weka.associations.FilteredAssociationRules

Set the rules to use.

setRuleset(ArrayList<Rule>) - Method in class weka.classifiers.rules.RuleStats

Set the ruleset of the stats, overwriting the old one if any

setRuleSetModel(RuleSetModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the ruleSetModel property.

setRulesMustContain(String) - Method in class weka.associations.FPGrowth

Set the comma separated list of items that rules must contain in order to be output.

setRunColumn(int) - Method in class weka.experiment.PairedTTester

Set the value of RunColumn.

setRunColumn(int) - Method in interface weka.experiment.Tester

Set the value of RunColumn.

setRunLower(int) - Method in class weka.experiment.Experiment

Set the lower run number for the experiment.

setRunLower(int) - Method in class weka.experiment.RemoteExperiment

Set the lower run number for the experiment.

setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Sets the number of runs

setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Sets the number of runs

setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Sets the m_nRuns.

setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Sets the number of runs

setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Sets the number of runs

setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Sets the number of runs

setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Sets the m_nRuns.

setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Sets the number of runs

setRunUpper(int) - Method in class weka.experiment.Experiment

Set the upper run number for the experiment.

setRunUpper(int) - Method in class weka.experiment.RemoteExperiment

Set the upper run number for the experiment.

setSample(Double) - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE

Sets the value of the sample property.

setSamplePeriod(int) - Method in class weka.gui.beans.StreamThroughput

Set the sampling period (in milliseconds) to compute througput over

setSampleSize(int) - Method in class weka.attributeSelection.ReliefFAttributeEval

Set the number of instances to sample for attribute estimation

setSampleSize(int) - Method in class weka.filters.unsupervised.instance.ReservoirSample

Sets the size of the subsample.

setSampleSizePercent(double) - Method in class weka.filters.supervised.instance.Resample

Sets the size of the subsample, as a percentage of the original set.

setSampleSizePercent(double) - Method in class weka.filters.unsupervised.instance.Resample

Sets the size of the subsample, as a percentage of the original set.

setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintableComponent

sets the title for the save dialog.

setSaveDialogTitle(String) - Method in interface weka.gui.visualize.PrintableHandler

sets the title for the save dialog

setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintablePanel

sets the title for the save dialog

setSaveForVisualization(boolean) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances

Sets whether the instances are saved for visualization or only evaluation of the prediction is to happen.

setSaveInstanceData(boolean) - Method in class weka.classifiers.trees.J48

Set whether instance data is to be saved.

setSaveInstanceData(boolean) - Method in class weka.clusterers.Cobweb

Set the value of saveInstances.

setSaveInstances(boolean) - Method in class weka.classifiers.trees.M5P

Set whether to save instance data at each node in the tree for visualization purposes

setSaverTemplate(Saver) - Method in class weka.gui.beans.Saver

Set the loader to use

setScale(double) - Method in class weka.filters.unsupervised.attribute.Normalize

Sets the scaling factor.

setScale(double, double) - Method in class weka.gui.visualize.JComponentWriter

sets the scale factor - is ignored since we always create a screenshot!

setScale(double, double) - Method in class weka.gui.visualize.PrintableComponent

sets the scale factor.

setScale(double, double) - Method in interface weka.gui.visualize.PrintableHandler

sets the scale factor

setScale(double, double) - Method in class weka.gui.visualize.PrintablePanel

sets the scale factor

setScaleWidthToFit(boolean) - Method in class weka.gui.DocumentPrinting

Sets whether to scale the width to fit.

setScalingEnabled(boolean) - Method in class weka.gui.visualize.JComponentWriter

sets whether to enable scaling

setScore(String) - Method in class weka.core.pmml.jaxbbindings.Node

Sets the value of the score property.

setScore(String) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the score property.

setScorecard(Scorecard) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the scorecard property.

setScoreType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

set quality measure to be used in searching for networks.

setSearch(ASSearch) - Method in class weka.attributeSelection.AttributeSelection

set the search method

setSearch(ASSearch) - Method in class weka.attributeSelection.CheckAttributeSelection

Set the search method to test.

setSearch(ASSearch) - Method in class weka.classifiers.meta.AttributeSelectedClassifier

Sets the search method

setSearch(ASSearch) - Method in class weka.classifiers.rules.DecisionTable

Sets the search method to use

setSearch(ASSearch) - Method in class weka.filters.supervised.attribute.AttributeSelection

Set search class

setSearchAlgorithm(SearchAlgorithm) - Method in class weka.classifiers.bayes.BayesNet

Set the SearchAlgorithm used in searching for network structures.

setSearchBackwards(boolean) - Method in class weka.attributeSelection.GreedyStepwise

Set whether to search backwards instead of forwards

setSearchString(String) - Method in class weka.gui.arffviewer.ArffTable

sets the search string to look for in the table, NULL or "" disables the search

setSearchTermination(int) - Method in class weka.attributeSelection.BestFirst

Set the numnber of non-improving nodes to consider before terminating search.

setSeasonalityExpoSmooth(SeasonalityExpoSmooth) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Sets the value of the seasonalityExpoSmooth property.

setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Sets index of the second value used.

setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues

Sets index of the second value used.

setSeed(int) - Method in class weka.attributeSelection.AttributeSelection

set the seed for use in cross validation

setSeed(int) - Method in class weka.attributeSelection.OneRAttributeEval

Set the random number seed for cross validation

setSeed(int) - Method in class weka.attributeSelection.ReliefFAttributeEval

Set the random number seed for randomly sampling instances.

setSeed(int) - Method in class weka.attributeSelection.WrapperSubsetEval

Set the seed to use for cross validation

setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.BVDecompose

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.BVDecomposeSegCVSub

Sets the random number seed

setSeed(int) - Method in class weka.classifiers.evaluation.EvaluationUtils

Sets the seed for randomization during cross-validation

setSeed(int) - Method in class weka.classifiers.functions.MultilayerPerceptron

This seeds the random number generator, that is used when a random number is needed for the network.

setSeed(int) - Method in class weka.classifiers.functions.supportVector.RegOptimizer

Sets the seed value for the random number generator

setSeed(int) - Method in class weka.classifiers.functions.VotedPerceptron

Set the value of Seed.

setSeed(int) - Method in class weka.classifiers.meta.MultiScheme

Sets the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableClassifier

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer

Set the seed for random number generation.

setSeed(long) - Method in class weka.classifiers.rules.JRip

Sets the seed value to use in randomizing the data

setSeed(int) - Method in class weka.classifiers.rules.PART

Set the value of Seed.

setSeed(int) - Method in class weka.classifiers.trees.J48

Set the value of Seed.

setSeed(int) - Method in class weka.classifiers.trees.RandomForest

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.trees.RandomTree

Set the seed for random number generation.

setSeed(int) - Method in class weka.classifiers.trees.REPTree

Set the value of Seed.

setSeed(int) - Method in class weka.clusterers.RandomizableClusterer

Set the seed for random number generation.

setSeed(int) - Method in class weka.clusterers.RandomizableDensityBasedClusterer

Set the seed for random number generation.

setSeed(int) - Method in class weka.clusterers.RandomizableSingleClustererEnhancer

Set the seed for random number generation.

setSeed(long) - Method in class weka.core.Debug.Random

Sets the seed of this random number generator using a single long seed.

setSeed(int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Sets the seed for random number generator (that is used for selecting the first anchor point randomly).

setSeed(int) - Method in interface weka.core.Randomizable

Set the seed for random number generation.

setSeed(int) - Method in class weka.core.TestInstances

sets the seed value for the random number generator

setSeed(int) - Method in class weka.datagenerators.DataGenerator

Sets the random number seed.

setSeed(long) - Method in class weka.filters.supervised.attribute.ClassOrder

Set randomization seed

setSeed(long) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Sets the random number seed for shuffling the dataset.

setSeed(int) - Method in class weka.filters.unsupervised.attribute.RandomProjection

Sets the random seed of the random number generator

setSeed(int) - Method in class weka.filters.unsupervised.attribute.RandomSubset

Set the seed value for the random number generator.

setSeed(long) - Method in class weka.filters.unsupervised.instance.RemoveFolds

Sets the random number seed for shuffling the dataset.

setSeed(int) - Method in class weka.gui.beans.CrossValidationFoldMaker

Set the seed

setSeed(int) - Method in class weka.gui.beans.TrainTestSplitMaker

Set the random seed

setSeed(int) - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Set a seed for random number generation (if needed).

setSeed(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Initializes a new random number generator using the supplied seed.

setSegmentId(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the segmentId property.

setSelectedAttributes(String) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

setSelectedAttributes(boolean[]) - Method in class weka.gui.AttributeSelectionPanel

Set the selected attributes in the widget.

setSelectedBeans(Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setSelectedBeans(int, Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setSelectedColumn(int) - Method in class weka.gui.arffviewer.ArffTable

sets the selected column

setSelectedRange(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Set the value of m_SelectedRange.

setSeperator(String) - Method in class weka.gui.HierarchyPropertyParser

Set the seperator between levels.

setSeqId(String) - Method in class weka.core.pmml.jaxbbindings.SequenceReference

Sets the value of the seqId property.

setSequenceModel(SequenceModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the sequenceModel property.

setSequenceReference(SequenceReference) - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence

Sets the value of the sequenceReference property.

setSequenceReference(SequenceReference) - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence

Sets the value of the sequenceReference property.

setSerializedClassifierFile(File) - Method in class weka.filters.supervised.attribute.AddClassification

Sets the file pointing to a serialized, trained classifier.

setSerializedClustererFile(File) - Method in class weka.filters.unsupervised.attribute.AddCluster

Sets the file pointing to a serialized, built clusterer.

setSetId(String) - Method in class weka.core.pmml.jaxbbindings.SetReference

Sets the value of the setId property.

setSetReference(SetReference) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the setReference property.

setShape(int) - Method in class weka.gui.treevisualizer.Node

Set the value of shape.

setShapes(ArrayList<ArrayList<Double>>) - Method in class weka.gui.visualize.VisualizePanel

This will set the shapes for the instances.

setShapeSize(int[]) - Method in class weka.gui.visualize.PlotData2D

Set the shape sizes for the plot data

setShapeSize(ArrayList<Object>) - Method in class weka.gui.visualize.PlotData2D

Set the shape sizes for the plot data

setShapeType(int[]) - Method in class weka.gui.visualize.PlotData2D

Set the shape type for the plot data

setShapeType(ArrayList<Integer>) - Method in class weka.gui.visualize.PlotData2D

Set the shape type for the plot data

setShowAttBars(boolean) - Method in class weka.gui.visualize.VisualizePanel

Set whether the attribute bars should be shown or not.

setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffPanel

Sets whether to display the attribute index in the header.

setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel

Sets whether to display the attribute index in the header.

setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffTableModel

Sets whether to display the attribute index in the header.

setShowAverage(boolean) - Method in class weka.experiment.ResultMatrix

sets whether to display the average per column or not.

setShowClassPanel(boolean) - Method in class weka.gui.visualize.VisualizePanel

Set whether the class panel should be shown or not.

setShowStdDev(boolean) - Method in class weka.experiment.ResultMatrix

sets whether to display the std deviations or not.

setShowStdDev(boolean) - Method in class weka.experiment.ResultMatrixSignificance

sets whether to display the std deviations or not - always false!

setShowStdDevs(boolean) - Method in class weka.experiment.PairedTTester

Set whether standard deviations are displayed or not.

setShowStdDevs(boolean) - Method in interface weka.experiment.Tester

Set whether standard deviations are displayed or not.

setShowZeroInstancesAsUnknown(boolean) - Method in class weka.gui.InstancesSummaryPanel

Set whether to show zero instances as unknown (i.e.

setShrinkage(double) - Method in class weka.classifiers.meta.AdditiveRegression

Set the shrinkage parameter

setShrinkage(double) - Method in class weka.classifiers.meta.LogitBoost

Set the value of Shrinkage.

setSigma(int) - Method in class weka.attributeSelection.ReliefFAttributeEval

Sets the sigma value.

setSigma(double) - Method in class weka.classifiers.functions.supportVector.Puk

Sets the sigma value.

setSignificance(int, int, int) - Method in class weka.experiment.ResultMatrix

sets the significance at the given position (if the position is valid).

setSignificanceLevel(double) - Method in class weka.associations.Apriori

Set the value of significanceLevel.

setSignificanceLevel(double) - Method in class weka.experiment.PairedTTester

Set the value of SignificanceLevel.

setSignificanceLevel(double) - Method in interface weka.experiment.Tester

Set the value of SignificanceLevel.

setSignificanceLevel(double) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Sets the significance level.

setSignificanceWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the significance (0 = optimal).

setSilent(boolean) - Method in class weka.core.AllJavadoc

sets whether to suppress output in the console

setSilent(boolean) - Method in class weka.core.Check

Set slient mode, i.e., no output at all to stdout

setSilent(boolean) - Method in class weka.core.Javadoc

sets whether to suppress output in the console

setSilent(boolean) - Method in class weka.estimators.CheckEstimator

Set slient mode, i.e., no output at all to stdout

setSimilarityScale(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringField

Sets the value of the similarityScale property.

setSimilarityType(String) - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity

Sets the value of the similarityType property.

setSimpleMatching(SimpleMatching) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the simpleMatching property.

setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the simplePredicate property.

setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Sets the value of the simplePredicate property.

setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the simplePredicate property.

setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the simplePredicate property.

setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the simpleSetPredicate property.

setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Sets the value of the simpleSetPredicate property.

setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the simpleSetPredicate property.

setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the simpleSetPredicate property.

setSIndex(int) - Method in class weka.gui.visualize.VisualizePanel

Set the shape for creating splits.

setSingle(String) - Method in class weka.gui.ResultHistoryPanel

Sets the single-click display to view the named result.

setSingleIndex(String) - Method in class weka.core.SingleIndex

Sets the index from a string representation.

setSingleLineCommentStart(String) - Method in class weka.gui.scripting.SyntaxDocument

Sets the string that is the start of a single-line comment.

setSize(int) - Method in class weka.core.matrix.DoubleVector

Sets the size of the vector

setSize(int) - Method in class weka.core.matrix.IntVector

Sets the size of the vector.

setSize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Cluster

Sets the value of the size property.

setSize(Double) - Method in class weka.core.pmml.jaxbbindings.Partition

Sets the value of the size property.

setSize(int, int) - Method in class weka.experiment.ResultMatrix

clears the content of the matrix and sets the new size.

setSkipIdentical(boolean) - Method in class weka.core.neighboursearch.LinearNNSearch

Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.

setSmoothedValue(Double) - Method in class weka.core.pmml.jaxbbindings.Level

Sets the value of the smoothedValue property.

setSmoothedValue(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Sets the value of the smoothedValue property.

setSmoothing(boolean) - Method in class weka.classifiers.trees.m5.Rule

Smooth predictions

setSMOReg(SMOreg) - Method in class weka.classifiers.functions.supportVector.RegOptimizer

sets the parent SVM

setSort(boolean) - Method in class weka.filters.unsupervised.attribute.AddValues

Sets whether the labels are sorted.

setSortColumn(int) - Method in class weka.experiment.PairedTTester

Set the column to sort on, -1 means the default sorting.

setSortColumn(int) - Method in interface weka.experiment.Tester

Set the column to sort on, -1 means the default sorting.

setSortDetails(String) - Method in class weka.gui.beans.Sorter

Set the sort rules to use

setSortType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.SortLabels

Sets the sort type to be used.

setSource(File) - Method in class weka.core.converters.AbstractFileLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(File) - Method in class weka.core.converters.AbstractLoader

Default implementation throws an IOException.

setSource(InputStream) - Method in class weka.core.converters.AbstractLoader

Default implementation throws an IOException.

setSource(URL) - Method in class weka.core.converters.ArffLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.ArffLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(File) - Method in class weka.core.converters.C45Loader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(InputStream) - Method in class weka.core.converters.CSVLoader

Resets the Loader object and sets the source of the data set to be the supplied Stream object.

setSource(File) - Method in class weka.core.converters.CSVLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(String, String, String) - Method in class weka.core.converters.DatabaseLoader

Sets the database url, user and pw

setSource(String) - Method in class weka.core.converters.DatabaseLoader

Sets the database url

setSource() - Method in class weka.core.converters.DatabaseLoader

Sets the database url using the DatabaseUtils file

setSource(File) - Method in class weka.core.converters.JSONLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(URL) - Method in class weka.core.converters.JSONLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.JSONLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(URL) - Method in class weka.core.converters.LibSVMLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.LibSVMLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(File) - Method in interface weka.core.converters.Loader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(InputStream) - Method in interface weka.core.converters.Loader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(URL) - Method in class weka.core.converters.MatlabLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.MatlabLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(InputStream) - Method in class weka.core.converters.SerializedInstancesLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(URL) - Method in class weka.core.converters.SVMLightLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.SVMLightLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(File) - Method in class weka.core.converters.TextDirectoryLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(File) - Method in class weka.core.converters.XRFFLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(URL) - Method in class weka.core.converters.XRFFLoader

Resets the Loader object and sets the source of the data set to be the supplied url.

setSource(InputStream) - Method in class weka.core.converters.XRFFLoader

Resets the Loader object and sets the source of the data set to be the supplied InputStream.

setSource(Node) - Method in class weka.gui.treevisualizer.Edge

Set the value of source.

setSourceCode(Classifier) - Method in class weka.classifiers.CheckSource

Sets the class to test.

setSourceCode(Filter) - Method in class weka.filters.CheckSource

Sets the class to test.

setSparseData(boolean) - Method in class weka.core.converters.DatabaseLoader

Sets whether data should be encoded as sparse instances

setSparseData(boolean) - Method in class weka.experiment.InstanceQuery

Sets whether data should be encoded as sparse instances

setSplitByDataSet(boolean) - Method in class weka.experiment.RemoteExperiment

Set whether sub experiments are to be created on the basis of data set.

setSplitCharacteristic(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the splitCharacteristic property.

setSplitCharacteristic(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel

Sets the value of the splitCharacteristic property.

setSplitConfidence(double) - Method in class weka.classifiers.trees.HoeffdingTree

Set the allowable error in a split decision.

setSplitCriterion(SelectedTag) - Method in class weka.classifiers.trees.HoeffdingTree

Set the split criterion to use (either Gini or info gain).

setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.CrossValidationResultProducer

Set the SplitEvaluator.

setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.ExplicitTestsetResultProducer

Set the SplitEvaluator.

setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.RandomSplitResultProducer

Set the SplitEvaluator.

setSplitOnResiduals(boolean) - Method in class weka.classifiers.trees.LMT

Set the value of splitOnResiduals.

setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split

Sets split point to greatest value in given data smaller or equal to old split point.

setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.C45Split

Sets split point to greatest value in given data smaller or equal to old split point.

setSplitPoint(double) - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Split point to be used for selection on numeric attribute.

setSpreadInitialCount(boolean) - Method in class weka.classifiers.trees.REPTree

Set the value of SpreadInitialCount.

setSqlWhere(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate

Sets the value of the sqlWhere property.

setSquaredEuclidean(SquaredEuclidean) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the squaredEuclidean property.

setSSB(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Sets the value of the ssb property.

setSSE(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality

Sets the value of the sse property.

setStandardDeviation(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo

Sets the value of the standardDeviation property.

setStandardDeviation(Double) - Method in class weka.core.pmml.jaxbbindings.Time

Sets the value of the standardDeviation property.

setStandardError(Double) - Method in class weka.core.pmml.jaxbbindings.TimeValue

Sets the value of the standardError property.

setStartEndIndices(int, int) - Method in class weka.core.neighboursearch.balltrees.BallNode

Sets the the start and end index of the portion of the master index array that is assigned to this node.

setStartSequentially(boolean) - Method in class weka.gui.beans.FlowRunner

Set whether to launch Startable beans one after the other or all in parallel.

setStartSet(String) - Method in class weka.attributeSelection.BestFirst

Sets a starting set of attributes for the search.

setStartSet(String) - Method in class weka.attributeSelection.GreedyStepwise

Sets a starting set of attributes for the search.

setStartSet(String) - Method in class weka.attributeSelection.Ranker

Sets a starting set of attributes for the search.

setStartSet(String) - Method in interface weka.attributeSelection.StartSetHandler

Sets a starting set of attributes for the search.

setStartTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Sets the value of the startTime property.

setStartTimeVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the startTimeVariable property.

setStatic() - Method in class weka.gui.beans.BeanVisual

Deprecated.

setStatus(int) - Method in class weka.gui.beans.IncrementalClassifierEvent

Set the status

setStatus(int) - Method in class weka.gui.beans.InstanceEvent

Set the status

setStatusFrequency(int) - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Set how often progress is reported to the status bar.

setStatusMessage(String) - Method in class weka.experiment.TaskStatusInfo

Set the status message.

setStatusVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the statusVariable property.

setStdDev(int, int, double) - Method in class weka.experiment.ResultMatrix

sets the std deviation at the given position (if the position is valid).

setStdDevPrec(int) - Method in class weka.experiment.ResultMatrix

sets the precision for the standard deviation.

setStdDevWidth(int) - Method in class weka.experiment.ResultMatrix

sets the width for the std dev (0 = optimal).

setStdError(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the stdError property.

setStemmer(Stemmer) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).

setStemmer(Stemmer) - Method in class weka.classifiers.functions.SGDText

the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).

setStemmer(String) - Method in class weka.core.stemmers.SnowballStemmer

sets the stemmer with the given name, e.g., "porter".

setStemmer(Stemmer) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).

setStepsize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Sets the value of the stepsize property.

setStepSize(int) - Method in class weka.experiment.LearningRateResultProducer

Set the value of StepSize.

setStopwords(File) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

sets the file containing the stopwords, null or a directory unset the stopwords.

setStopwords(File) - Method in class weka.classifiers.functions.SGDText

sets the file containing the stopwords, null or a directory unset the stopwords.

setStopwords(File) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

sets the file containing the stopwords, null or a directory unset the stopwords.

setStringAttributes(String) - Method in class weka.core.converters.CSVLoader

Sets the attribute range to be forced to type string.

setStringValue(String) - Method in class weka.core.Attribute

Clear the map and list of values and set them to contain just the supplied value

setStroke(Stroke) - Method in class weka.gui.visualize.PostscriptGraphics

setStructure(Instances) - Method in class weka.core.converters.AbstractSaver

Sets the strcuture of the instances for the first step of incremental saving.

setStructure(Instances) - Method in class weka.gui.beans.IncrementalClassifierEvent

Set the instances structure

setStructure(Instances) - Method in class weka.gui.beans.InstanceEvent

Set the instances structure

setSubFlow(Vector<Object>) - Method in class weka.gui.beans.MetaBean

setSubFlowPreview(ImageIcon) - Method in class weka.gui.beans.MetaBean

setSubjectIDVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the subjectIDVariable property.

setSubsequenceLength(int) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets the length of the subsequence.

setSubSpaceSize(double) - Method in class weka.classifiers.meta.RandomSubSpace

Sets the size of each subSpace, as a percentage of the training set size.

setSubtreeRaising(boolean) - Method in class weka.classifiers.trees.J48

Set the value of subtreeRaising.

setSummary(int[][], int[][]) - Method in class weka.experiment.ResultMatrix

sets the non-significant and significant wins of the resultsets.

setSumOfSquares(double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the sumOfSquares property.

setSumSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the sumSquaredError property.

setSumSquaredRegression(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the sumSquaredRegression property.

setSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule

Sets the value of the support property.

setSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.Itemset

Sets the value of the support property.

setSupport(Double) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the support property.

setSupport(double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule

Sets the value of the support property.

setSupportVectorMachineModel(SupportVectorMachineModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the supportVectorMachineModel property.

setSupportVectors(SupportVectors) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Sets the value of the supportVectors property.

setSuppressErrorMessage(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegression

Turn off the error message that is reported when no useful attribute is found.

setSuppressMappingReport(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier

Set whether to suppress output the report of model to input mappings.

setSuppressOutput(boolean) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Sets whether to the regular output is suppressed in case the output is stored in a file.

setSvmRepresentation(SVMREPRESENTATION) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the svmRepresentation property.

setSymbols(HashMap<String, Double>) - Method in class weka.core.mathematicalexpression.Parser

Sets the variable - value relation to use.

setSymbols(HashMap) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Sets the variable - value relation to use.

setT1(double) - Method in class weka.clusterers.Canopy

Set the T1 distance.

setT2(double) - Method in class weka.clusterers.Canopy

Set the T2 distance to use.

setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.ChildParent

Sets the value of the tableLocator property.

setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.MapValues

Sets the value of the tableLocator property.

setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances

Sets the value of the tableLocator property.

setTableName(String) - Method in class weka.core.converters.DatabaseSaver

Sets the table's name.

setTabs(int) - Method in class weka.gui.scripting.SyntaxDocument

sets the number of characters per tab.

setTabTitle(String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setTabTitle(int, String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setTabuList(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch

Sets the Tabu List length.

setTabuList(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

Sets the Tabu List length.

setTanimoto(Tanimoto) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure

Sets the value of the tanimoto property.

setTarget(String) - Method in class weka.core.pmml.jaxbbindings.Anova

Sets the value of the target property.

setTarget(Object) - Method in class weka.gui.PropertySheetPanel

Sets a new target object for customisation.

setTarget(Node) - Method in class weka.gui.treevisualizer.Edge

Set the value of target.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStats

Sets the value of the targetCategory property.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PCell

Sets the value of the targetCategory property.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the targetCategory property.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PPCell

Sets the value of the targetCategory property.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.RegressionTable

Sets the value of the targetCategory property.

setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Sets the value of the targetCategory property.

setTargetField(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the targetField property.

setTargetField(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality

Sets the value of the targetField property.

setTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the targetFieldDisplayValue property.

setTargetFieldName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel

Sets the value of the targetFieldName property.

setTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.LiftData

Sets the value of the targetFieldValue property.

setTargetReferenceCategory(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the targetReferenceCategory property.

setTargets(Targets) - Method in class weka.core.pmml.jaxbbindings.DecisionTree

Sets the value of the targets property.

setTargets(Targets) - Method in class weka.core.pmml.jaxbbindings.Regression

Sets the value of the targets property.

setTargetValueCounts(TargetValueCounts) - Method in class weka.core.pmml.jaxbbindings.BayesOutput

Sets the value of the targetValueCounts property.

setTargetValueCounts(TargetValueCounts) - Method in class weka.core.pmml.jaxbbindings.PairCounts

Sets the value of the targetValueCounts property.

setTargetVariableName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the targetVariableName property.

setTaskResult(Object) - Method in class weka.experiment.TaskStatusInfo

Set the returnable result for this task..

setTaxonomy(String) - Method in class weka.core.pmml.jaxbbindings.DataField

Sets the value of the taxonomy property.

setTaxonomy(Taxonomy) - Method in class weka.core.pmml.jaxbbindings.TextDictionary

Sets the value of the taxonomy property.

setTCol(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the tCol property.

setTempDirectory(String) - Method in class weka.gui.beans.Sorter

Set the directory to use for temporary files during incremental operation

setTestBaseFromDialog() - Method in class weka.gui.experiment.ResultsPanel

setTestEvaluator(boolean) - Method in class weka.attributeSelection.CheckAttributeSelection

Sets whether the evaluator or the search method is being tested.

setTestSet(DataSetEvent) - Method in class weka.gui.beans.BatchClassifierEvent

Set the test set

setTestsetDir(File) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the directory to use for the test sets.

setTestsetPrefix(String) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the prefix to use for the test sets.

setTestsetSuffix(String) - Method in class weka.experiment.ExplicitTestsetResultProducer

Sets the suffix to use for the test sets.

setTestStatistic(BASELINETESTSTATISTIC) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the testStatistic property.

setTestStructure(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier

Set the test structure (if known in advance) that we are likely to see.

setTestWithFailAlwaysSucceeds(boolean) - Method in class weka.core.Capabilities

Whether test with fail should always succeed.

setText(String) - Method in class weka.gui.beans.BeanVisual

Set the label for the visual.

setText(String) - Method in class weka.gui.beans.EnvironmentField

Set the text to display in the editable combo box.

setTextModel(TextModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the textModel property.

setTFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.

setThreshold(double) - Method in class weka.attributeSelection.GreedyStepwise

Set the threshold by which the AttributeSelection module can discard attributes.

setThreshold(double) - Method in interface weka.attributeSelection.RankedOutputSearch

Sets a threshold by which attributes can be discarded from the ranking.

setThreshold(double) - Method in class weka.attributeSelection.Ranker

Set the threshold by which the AttributeSelection module can discard attributes.

setThreshold(double) - Method in class weka.attributeSelection.WrapperSubsetEval

Set the value of the threshold for repeating cross validation

setThreshold(double) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel

Sets the value of the threshold property.

setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel

Sets the value of the threshold property.

setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the threshold property.

setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the threshold property.

setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine

Sets the value of the threshold property.

setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

Sets the value of the threshold property.

setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Sets the threshold for the max error when predicting a numeric class.

setTime(Time) - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence

Sets the value of the time property.

setTime(double) - Method in class weka.core.pmml.jaxbbindings.BaselineCell

Sets the value of the time property.

setTime(Time) - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence

Sets the value of the time property.

setTime(Time) - Method in class weka.core.pmml.jaxbbindings.Sequence

Sets the value of the time property.

setTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeValue

Sets the value of the time property.

setTimeAnchor(TimeAnchor) - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Sets the value of the timeAnchor property.

setTimes(int, double) - Method in class weka.core.matrix.DoubleVector

Multiplies a value to an element

setTimeSeriesModel(TimeSeriesModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the timeSeriesModel property.

setTimestamp(Timestamp) - Method in class weka.core.pmml.jaxbbindings.Header

Sets the value of the timestamp property.

setTimestamp(Timestamp) - Method in class weka.core.pmml.jaxbbindings.TimeValue

Sets the value of the timestamp property.

setTokenizer(Tokenizer) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

the tokenizer algorithm to use.

setTokenizer(Tokenizer) - Method in class weka.classifiers.functions.SGDText

the tokenizer algorithm to use.

setTokenizer(Tokenizer) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

the tokenizer algorithm to use.

setTolerance(double) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

sets the tolerance

setToleranceParameter(double) - Method in class weka.classifiers.functions.SMO

Set the value of tolerance parameter.

setToolTipText(String) - Method in class weka.gui.GenericObjectEditor.GOETreeNode

Set the tool tip for this node

setTop(double) - Method in class weka.gui.treevisualizer.Node

Set the value of top.

setTotalFreq(double) - Method in class weka.core.pmml.jaxbbindings.Counts

Sets the value of the totalFreq property.

setTotalSquaresSum(Double) - Method in class weka.core.pmml.jaxbbindings.ContStats

Sets the value of the totalSquaresSum property.

setTotalValuesSum(Double) - Method in class weka.core.pmml.jaxbbindings.ContStats

Sets the value of the totalValuesSum property.

setTrainingData(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the training data to use

setTrainingTime(int) - Method in class weka.classifiers.functions.MultilayerPerceptron

Set the number of training epochs to perform.

setTrainIterations(int) - Method in class weka.classifiers.BVDecompose

Sets the maximum number of boost iterations

setTrainPercent(double) - Method in class weka.experiment.RandomSplitResultProducer

Set the value of TrainPercent.

setTrainPercent(double) - Method in class weka.gui.beans.TrainTestSplitMaker

Set the percentage of data to be in the training portion of the split

setTrainPoolSize(int) - Method in class weka.classifiers.BVDecompose

Set the number of instances in the training pool.

setTrainSet(DataSetEvent) - Method in class weka.gui.beans.BatchClassifierEvent

Set the training set

setTrainSize(int) - Method in class weka.classifiers.BVDecomposeSegCVSub

Set the training size.

setTransactionsMustContain(String) - Method in class weka.associations.FPGrowth

Set the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.

setTransform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics

setTransformAllValues(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary

Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.

setTransformAllValues(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary

Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.

setTransformation(String) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Sets the value of the transformation property.

setTransformationDictionary(TransformationDictionary) - Method in class weka.core.pmml.jaxbbindings.PMML

Sets the value of the transformationDictionary property.

setTransformBackToOriginal(boolean) - Method in class weka.attributeSelection.PrincipalComponents

Sets whether the data should be transformed back to the original space

setTranslation(double) - Method in class weka.filters.unsupervised.attribute.Normalize

Sets the translation.

setTreatMissingValuesAsZero(boolean) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse

Set whether missing values should be treated in the same way as zeros

setTreatZeroAsMissing(boolean) - Method in class weka.associations.Apriori

Sets whether zeros (i.e.

setTreeModel(TreeModel) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the treeModel property.

setTrend(String) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth

Sets the value of the trend property.

setTrendExpoSmooth(TrendExpoSmooth) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing

Sets the value of the trendExpoSmooth property.

setTrialsValue(BigInteger) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the trialsValue property.

setTrialsVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel

Sets the value of the trialsVariable property.

setTrim(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier

Set whether to trim white space from each end of names before matching.

setTRow(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the tRow property.

setTrue(True) - Method in class weka.core.pmml.jaxbbindings.Attribute

Sets the value of the true property.

setTrue(True) - Method in class weka.core.pmml.jaxbbindings.CompoundRule

Sets the value of the true property.

setTrue(True) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the true property.

setTrue(True) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the true property.

setTrueNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats

Sets the number of negative instances predicted as negative

setTruePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats

Sets the number of positive instances predicted as positive

setTrueStepName(String) - Method in class weka.gui.beans.FlowByExpression

Set the name of the connected step to send "true" instances to

setTruncate(boolean) - Method in class weka.core.converters.DatabaseSaver

Set whether to truncate (i.e.

setTStart(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

Sets the m_fTStart.

setTStart(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

Sets the m_fTStart.

setTValue(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat

Sets the value of the tValue property.

setType(int) - Method in class weka.classifiers.functions.neural.NeuralConnection

setType(String) - Method in class weka.core.pmml.jaxbbindings.AnovaRow

Sets the value of the type property.

setType(String) - Method in class weka.core.pmml.jaxbbindings.ArrayType

Sets the value of the type property.

setType(String) - Method in class weka.core.pmml.jaxbbindings.PCovMatrix

Sets the value of the type property.

setType(String) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the type property.

setType(TIMEANCHOR2) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor

Sets the value of the type property.

setType(VALIDTIMESPEC) - Method in class weka.core.pmml.jaxbbindings.TimeCycle

Sets the value of the type property.

setType(TIMEEXCEPTIONTYPE) - Method in class weka.core.pmml.jaxbbindings.TimeException

Sets the value of the type property.

setType(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Set the type of the new attribute

setUndoBuffer(Stack<File>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setUndoBuffer(int, Stack<File>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

setUndoEnabled(boolean) - Method in interface weka.core.Undoable

sets whether undo support is enabled

setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffPanel

sets whether undo support is enabled

setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel

sets whether undo support is enabled

setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel

sets whether undo support is enabled

setUniformDistribution(UniformDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate

Sets the value of the uniformDistribution property.

setUniformDistribution(UniformDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline

Sets the value of the uniformDistribution property.

setUnit(String) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth

Sets the value of the unit property.

setUnpruned(boolean) - Method in class weka.classifiers.rules.PART

Set the value of unpruned.

setUnpruned(boolean) - Method in class weka.classifiers.trees.J48

Set the value of unpruned.

setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.M5Base

Use unpruned tree/rules

setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.Rule

Use unpruned tree/rules

setUp() - Method in class weka.gui.explorer.AbstractPlotInstances

Performs checks, sets up the structure for the plot instances.

setupAttribLists() - Method in class weka.gui.visualize.MatrixPanel

Sets up the UI's attributes lists

setUpBoundaryPanel() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Sets up the BoundaryPanel object so that it is ready for plotting.

setUpComboBoxes(Instances) - Method in class weka.gui.visualize.ThresholdVisualizePanel

This overloads VisualizePanel's setUpComboBoxes to add ActionListeners to watch for when the X/Y Axis comboboxes are changed.

setUpComboBoxes(Instances) - Method in class weka.gui.visualize.VisualizePanel

initializes the comboboxes based on the data

setUpdateIncrementalClassifier(boolean) - Method in class weka.gui.beans.Classifier

Set whether an incremental classifier will be updated on the incoming instance stream.

setUpdateWeightsOnly(boolean) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator

Sets whether only weights should be udpated.

setUpFile() - Method in class weka.gui.beans.LoaderCustomizer

setUpFile() - Method in class weka.gui.beans.SaverCustomizer

Sets up dialog for saving instances in a file

setUpFile() - Method in class weka.gui.beans.SerializedModelSaverCustomizer

Sets up dialog for saving models to a file

SetupModePanel - Class in weka.gui.experiment

This panel switches between simple and advanced experiment setup panels.

SetupModePanel() - Constructor for class weka.gui.experiment.SetupModePanel

Creates the setup panel with no initial experiment.

SetupPanel - Class in weka.gui.experiment

This panel controls the configuration of an experiment.

SetupPanel(Experiment) - Constructor for class weka.gui.experiment.SetupPanel

Creates the setup panel with the supplied initial experiment.

SetupPanel() - Constructor for class weka.gui.experiment.SetupPanel

Creates the setup panel with no initial experiment.

setUpper(double) - Method in class weka.core.pmml.jaxbbindings.UniformDistribution

Sets the value of the upper property.

setUpper(int) - Method in class weka.core.Range

Sets the value of "last".

setUpper(int) - Method in class weka.core.SingleIndex

Sets the value of "last".

setUpperBoundMinSupport(double) - Method in class weka.associations.Apriori

Set the value of upperBoundMinSupport.

setUpperBoundMinSupport(double) - Method in class weka.associations.FPGrowth

Set the value of upperBoundMinSupport.

setUpperSize(int) - Method in class weka.experiment.LearningRateResultProducer

Set the value of UpperSize.

setURL(String) - Method in class weka.core.converters.ArffLoader

Set the url to load from

setUrl(String) - Method in interface weka.core.converters.DatabaseConverter

setUrl(String) - Method in class weka.core.converters.DatabaseLoader

Sets the database URL

setUrl(String) - Method in class weka.core.converters.DatabaseSaver

Sets the database URL.

setURL(String) - Method in class weka.core.converters.JSONLoader

Set the url to load from.

setURL(String) - Method in class weka.core.converters.LibSVMLoader

Set the url to load from.

setURL(String) - Method in class weka.core.converters.MatlabLoader

Set the url to load from.

setURL(String) - Method in class weka.core.converters.SVMLightLoader

Set the url to load from.

setURL(String) - Method in interface weka.core.converters.URLSourcedLoader

Set the url to load from

setURL(String) - Method in class weka.core.converters.XRFFLoader

Set the url to load from

setURL(String) - Method in class weka.gui.sql.ConnectionPanel

sets the URL.

setUsage(TIMESERIESUSAGE) - Method in class weka.core.pmml.jaxbbindings.TimeSeries

Sets the value of the usage property.

setUsageType(FIELDUSAGETYPE) - Method in class weka.core.pmml.jaxbbindings.MiningField

Sets the value of the usageType property.

setUseADTree(boolean) - Method in class weka.classifiers.bayes.BayesNet

Set whether ADTree structure is used or not

setUseAIC(boolean) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of useAIC.

setUseAIC(boolean) - Method in class weka.classifiers.trees.lmt.LogisticBase

Set the value of useAIC.

setUseAIC(boolean) - Method in class weka.classifiers.trees.LMT

Set the value of useAIC.

setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber

set use the arc reversal operation

setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber

set use the arc reversal operation

setUseBetterEncoding(boolean) - Method in class weka.filters.supervised.attribute.Discretize

Sets whether better encoding is to be used for MDL.

setUseBinNumbers(boolean) - Method in class weka.filters.supervised.attribute.Discretize

Sets whether bin numbers rather than ranges should be used for discretized attributes.

setUseBinNumbers(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize

Sets whether bin numbers rather than ranges should be used for discretized attributes.

setUseBlanks(boolean) - Method in class weka.gui.scripting.SyntaxDocument

Sets whether to use blanks instead of tabs.

setUseConjugateGradientDescent(boolean) - Method in class weka.classifiers.functions.Logistic

Sets whether conjugate gradient descent is used.

setUseCpuTime(boolean) - Method in class weka.core.Debug.Clock

enables/disables the use of CPU time (if measurement of CPU time is available).

setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

setUseCrossValidation(boolean) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of useCrossValidation.

setUseCustomDimensions(boolean) - Method in class weka.gui.visualize.JComponentWriter

sets whether to use custom dimensions for the image

setUseDouble(boolean) - Method in class weka.core.converters.MatlabSaver

Sets whether to use double or single precision.

setUseEqualFrequency(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization

Set the value of UseEqualFrequency.

setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize

Set the value of UseEqualFrequency.

setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Set the value of UseEqualFrequency.

setUseIBk(boolean) - Method in class weka.classifiers.rules.DecisionTable

Sets whether IBk should be used instead of the majority class

setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator

Sets the UseK2Prior.

setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator

Sets the UseK2Prior.

setUseKernelEstimator(boolean) - Method in class weka.classifiers.bayes.NaiveBayes

Sets if kernel estimator is to be used.

setUseKononenko(boolean) - Method in class weka.filters.supervised.attribute.Discretize

Sets whether Kononenko's MDL criterion is to be used.

setUseLaplace(boolean) - Method in class weka.classifiers.trees.J48

Set the value of useLaplace.

setUseLeastValues(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues

Sets whether to use values with least or most instances

setUseLowerOrder(boolean) - Method in class weka.classifiers.functions.supportVector.PolyKernel

Sets whether to use lower-order terms.

setUseMDLcorrection(boolean) - Method in class weka.classifiers.rules.PART

Set the value of useMDLcorrection.

setUseMDLcorrection(boolean) - Method in class weka.classifiers.trees.J48

Set the value of useMDLcorrection.

setUseMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise

Sets the flag if missing values are treated as extra values.

setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

setUseNormalization(boolean) - Method in class weka.classifiers.functions.supportVector.StringKernel

Sets whether to use normalization.

setUseORForMustContainList(boolean) - Method in class weka.associations.FPGrowth

Set whether to use OR rather than AND when considering must contain lists.

setUsePairwiseCoupling(boolean) - Method in class weka.classifiers.meta.MultiClassClassifier

Set whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.

setUseProb(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

setUsePropertyIterator(boolean) - Method in class weka.experiment.Experiment

Sets whether the custom property iterator should be used.

setUsePropertyIterator(boolean) - Method in class weka.experiment.RemoteExperiment

Sets whether the custom property iterator should be used.

setUsePruning(boolean) - Method in class weka.classifiers.rules.JRip

Sets whether pruning is performed

setUser(String) - Method in interface weka.core.converters.DatabaseConverter

setUser(String) - Method in class weka.core.converters.DatabaseLoader

Sets the database user

setUser(String) - Method in class weka.core.converters.DatabaseSaver

Sets the database user.

setUser(String) - Method in class weka.gui.sql.ConnectionPanel

sets the User.

setUseReasonCodes(Boolean) - Method in class weka.core.pmml.jaxbbindings.Scorecard

Sets the value of the useReasonCodes property.

setUseRelativePath(boolean) - Method in class weka.core.converters.AbstractFileLoader

Set whether to use relative rather than absolute paths

setUseRelativePath(boolean) - Method in class weka.core.converters.AbstractFileSaver

Set whether to use relative rather than absolute paths

setUseRelativePath(boolean) - Method in interface weka.core.converters.FileSourcedConverter

Set whether to use relative rather than absolute paths

setUseRelativePath(boolean) - Method in class weka.gui.beans.SerializedModelSaver

Set whether to use relative paths for the directory.

setUseResampling(boolean) - Method in class weka.classifiers.meta.AdaBoostM1

Set resampling mode

setUseResampling(boolean) - Method in class weka.classifiers.meta.LogitBoost

Set resampling mode

setUsername(String) - Method in class weka.experiment.DatabaseUtils

Set the database username.

setUserOptions(String[]) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation

sets the option the user supplied for the kernel

setUserOptions(String[]) - Method in class weka.core.CheckOptionHandler

Sets the user-supplied options (creates a copy)

setUseShortIdentifiers(boolean) - Method in class weka.filters.supervised.attribute.MergeNominalValues

Set whether to output short identifiers for merged values.

setUseStars(boolean) - Method in class weka.core.AllJavadoc

sets whether to prefix the Javadoc with "*"

setUseStars(boolean) - Method in class weka.core.Javadoc

sets whether to prefix the Javadoc with "*"

setUseStopList(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set whether to ignore all words that are on the stoplist.

setUseStopList(boolean) - Method in class weka.classifiers.functions.SGDText

Set whether to ignore all words that are on the stoplist.

setUseStoplist(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets whether if the words that are on a stoplist are to be ignored (The stop list is in weka.core.StopWords).

setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayes

Set whether supervised discretization is to be used.

setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayesUpdateable

Set whether supervised discretization is to be used.

setUseTab(boolean) - Method in class weka.classifiers.evaluation.output.prediction.CSV

Sets whether to use tab instead of comma as separator.

setUseTabs(boolean) - Method in class weka.core.converters.MatlabSaver

Sets whether to use tabs instead of blanks.

setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch

setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch

setUseTree(boolean) - Method in class weka.classifiers.trees.m5.Rule

Use an m5 tree rather than generate rules

setUseUnsmoothed(boolean) - Method in class weka.classifiers.trees.m5.M5Base

Use unsmoothed predictions

setUseVariant1(boolean) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved

Sets whether to use variant 1

setUseWordFrequencies(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Set whether to use word frequencies rather than binary bag of words representation.

setUseWordFrequencies(boolean) - Method in class weka.classifiers.functions.SGDText

Set whether to use word frequencies rather than binary bag of words representation.

setValidating(boolean) - Method in class weka.core.xml.XMLDocument

sets whether to use a validating parser or not.
Note: this does clear the current DOM document!

setValidating(boolean) - Method in class weka.core.xml.XMLOptions

sets whether to use a validating parser or not.

setValidationSetSize(int) - Method in class weka.classifiers.functions.MultilayerPerceptron

This will set the size of the validation set.

setValidationThreshold(int) - Method in class weka.classifiers.functions.MultilayerPerceptron

This sets the threshold to use for when validation testing is being done.

setValue(int, String) - Method in class weka.core.AbstractInstance

Sets a value of a nominal or string attribute to the given value.

setValue(Attribute, double) - Method in class weka.core.AbstractInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(Attribute, String) - Method in class weka.core.AbstractInstance

Sets a value of an nominal or string attribute to the given value.

setValue(int, double) - Method in class weka.core.BinarySparseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(int, double) - Method in class weka.core.DenseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(int, double) - Method in interface weka.core.Instance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(int, String) - Method in interface weka.core.Instance

Sets a value of a nominal or string attribute to the given value.

setValue(Attribute, double) - Method in interface weka.core.Instance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(Attribute, String) - Method in interface weka.core.Instance

Sets a value of an nominal or string attribute to the given value.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Category

Sets the value of the value property.

setValue(Double) - Method in class weka.core.pmml.jaxbbindings.Coefficient

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Constant

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Decision

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Extension

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.FieldValue

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Item

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.MatCell

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.OutputField

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.PairCounts

Sets the value of the value property.

setValue(double) - Method in class weka.core.pmml.jaxbbindings.PCovCell

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.PPCell

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.ResultField

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValue

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValueCount

Sets the value of the value property.

setValue(double) - Method in class weka.core.pmml.jaxbbindings.TimeValue

Sets the value of the value property.

setValue(String) - Method in class weka.core.pmml.jaxbbindings.Value

Sets the value of the value property.

setValue(Object, PropertyPath.Path, Object) - Static method in class weka.core.PropertyPath

set the given value specified by the given path in the object

setValue(Object, String, Object) - Static method in class weka.core.PropertyPath

set the given value specified by the given path in the object

setValue(int, double) - Method in class weka.core.SparseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(TechnicalInformation.Field, String) - Method in class weka.core.TechnicalInformation

sets the value for the given field, overwrites any previously existing one.

setValue(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec

Set the value of the new attribute.

setValue(Object) - Method in class weka.gui.beans.EnvironmentField

setValue(Object) - Method in class weka.gui.CostMatrixEditor

Sets the value of the CostMatrix to be edited.

setValue(Object) - Method in class weka.gui.GenericArrayEditor

Sets the current object array.

setValue(Object) - Method in class weka.gui.GenericObjectEditor

Sets the current Object.

setValue(Object) - Method in class weka.gui.SimpleDateFormatEditor

Sets the value of the date format to be edited.

setValueAt(Object, int, int) - Method in class weka.gui.arffviewer.ArffTableModel

sets the value in the cell at columnIndex and rowIndex to aValue.

setValueAt(Object, int, int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel

sets the value in the cell at columnIndex and rowIndex to aValue.

setValueAt(Object, int, int) - Method in class weka.gui.beans.InteractiveTableModel

setValueAt(Object, int, int) - Method in class weka.gui.SortedTableModel

Sets the value in the cell at columnIndex and rowIndex to aValue.

setValueAt(Object, int, int) - Method in class weka.gui.sql.ResultSetTableModel

sets the value in the cell at columnIndex and rowIndex to aValue.

setValueIndex(int) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Sets index of the indicator value.

setValueIndices(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Sets indices of the indicator values.

setValueIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator

Set which attributes are to be deleted (or kept if invert is true)

setValueReplacements(String) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues

setValuesList(String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the ranges for each attribute.

setValuesList(String, double[], double[], String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Sets the ranges for each attribute.

setValueSparse(int, double) - Method in class weka.core.BinarySparseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValueSparse(int, double) - Method in class weka.core.DenseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValueSparse(int, double) - Method in interface weka.core.Instance

Sets a specific value in the instance to the given value (internal floating-point format), given an index into the sparse representation.

setValueSparse(int, double) - Method in class weka.core.SparseInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setVariance(double) - Method in class weka.core.pmml.jaxbbindings.AnyDistribution

Sets the value of the variance property.

setVariance(double) - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution

Sets the value of the variance property.

setVarianceCovered(double) - Method in class weka.attributeSelection.PrincipalComponents

Sets the amount of variance to account for when retaining principal components

setVarianceCovered(double) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents

Sets the amount of variance to account for when retaining principal components.

setVectorFields(VectorFields) - Method in class weka.core.pmml.jaxbbindings.VectorDictionary

Sets the value of the vectorFields property.

setVectorId(String) - Method in class weka.core.pmml.jaxbbindings.SupportVector

Sets the value of the vectorId property.

setVerbose(boolean) - Method in class weka.associations.Apriori

Sets verbose mode

setVerboseOn() - Method in class weka.core.Debug.DBO

Set the verbose on flag on

setVerificationFields(VerificationFields) - Method in class weka.core.pmml.jaxbbindings.ModelVerification

Sets the value of the verificationFields property.

setVersion(String) - Method in class weka.core.pmml.jaxbbindings.Application

Sets the value of the version property.

setVersion(String) - Method in class weka.core.pmml.jaxbbindings.PMML

Sets the value of the version property.

setVisible(boolean) - Method in class weka.gui.Main

Shows or hides this component depending on the value of parameter b.

setVisible(boolean) - Method in class weka.gui.sql.SqlViewerDialog

displays the dialog if TRUE.

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSink

Set the visual for this data source

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSource

Set the visual for this data source

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractEvaluator

Set the visual

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTestSetProducer

Set the visual for this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Set the visual for this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainingSetProducer

Set the visual for this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.Appender

Set a new visual representation

setVisual(BeanVisual) - Method in class weka.gui.beans.Associator

Sets the visual appearance of this wrapper bean

setVisual(BeanVisual) - Method in class weka.gui.beans.ClassAssigner

setVisual(BeanVisual) - Method in class weka.gui.beans.Classifier

Sets the visual appearance of this wrapper bean

setVisual(BeanVisual) - Method in class weka.gui.beans.ClassValuePicker

setVisual(BeanVisual) - Method in class weka.gui.beans.Clusterer

Sets the visual appearance of this wrapper bean

setVisual(BeanVisual) - Method in class weka.gui.beans.CostBenefitAnalysis

setVisual(BeanVisual) - Method in class weka.gui.beans.DataVisualizer

Set the visual appearance of this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.Filter

Set the visual appearance of this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.FlowByExpression

setVisual(BeanVisual) - Method in class weka.gui.beans.GraphViewer

Set the visual appearance of this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.ImageSaver

setVisual(BeanVisual) - Method in class weka.gui.beans.ImageViewer

setVisual(BeanVisual) - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Sets the visual appearance of this wrapper bean

setVisual(BeanVisual) - Method in class weka.gui.beans.Join

Set the visual for this step

setVisual(BeanVisual) - Method in class weka.gui.beans.MetaBean

Sets the visual appearance of this wrapper bean

setVisual(BeanVisual) - Method in class weka.gui.beans.ModelPerformanceChart

Set the visual appearance of this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.PredictionAppender

Set the visual for this data source

setVisual(BeanVisual) - Method in class weka.gui.beans.SerializedModelSaver

Set the visual for this data source.

setVisual(BeanVisual) - Method in class weka.gui.beans.Sorter

Set a new visual representation

setVisual(BeanVisual) - Method in class weka.gui.beans.StripChart

Set the visual appearance of this bean

setVisual(BeanVisual) - Method in class weka.gui.beans.SubstringLabeler

Set a new visual representation

setVisual(BeanVisual) - Method in class weka.gui.beans.SubstringReplacer

Set a new visual representation

setVisual(BeanVisual) - Method in class weka.gui.beans.TextSaver

setVisual(BeanVisual) - Method in class weka.gui.beans.TextViewer

Describe setVisual method here.

setVisual(BeanVisual) - Method in interface weka.gui.beans.Visible

Set a new visual representation

setVoteFlag(boolean) - Method in class weka.datagenerators.classifiers.classification.RDG1

Sets the vote flag.

setWeight(double) - Method in class weka.core.AbstractInstance

Sets the weight of an instance.

setWeight(double) - Method in class weka.core.Attribute

Sets the new attribute's weight

setWeight(double) - Method in interface weka.core.Instance

Sets the weight of an instance.

setWeight(double) - Method in class weka.core.pmml.jaxbbindings.Con1

Sets the value of the weight property.

setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.Item

Sets the value of the weight property.

setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.Segment

Sets the value of the weight property.

setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule

Sets the value of the weight property.

setWeightByDistance(boolean) - Method in class weka.attributeSelection.ReliefFAttributeEval

Set the nearest neighbour weighting method

setWeighted(String) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats

Sets the value of the weighted property.

setWeighted(String) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats

Sets the value of the weighted property.

setWeightField(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the weightField property.

setWeightingDimensions(boolean[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Set the dimensions to be used in computing a weight for each instance generated

setWeightingDimensions(boolean[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Set which dimensions to use when computing a weight for the next instance to generate

setWeightingKernel(int) - Method in class weka.classifiers.lazy.LWL

Sets the kernel weighting method to use.

setWeightingValues(double[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Set the values of the dimensions (chosen via setWeightingDimensions) to be used when computing instance weights

setWeightingValues(double[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Set the values for the weighting dimensions to be used when computing the weight for the next instance to be generated

setWeightThreshold(int) - Method in class weka.classifiers.meta.AdaBoostM1

Set weight threshold

setWeightThreshold(int) - Method in class weka.classifiers.meta.LogitBoost

Set weight thresholding

setWeightTrimBeta(double) - Method in class weka.classifiers.functions.SimpleLogistic

Set the value of weightTrimBeta.

setWeightTrimBeta(double) - Method in class weka.classifiers.trees.lmt.LogisticBase

Sets the option "weightTrimBeta".

setWeightTrimBeta(double) - Method in class weka.classifiers.trees.LMT

Set the value of weightTrimBeta.

setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer

Sets the value of the width property.

setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork

Sets the value of the width property.

setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron

Sets the value of the width property.

setWindowSize(int) - Method in class weka.classifiers.lazy.IBk

Sets the maximum number of instances allowed in the training pool.

setWindowSize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TestDistributions

Sets the value of the windowSize property.

setWords(String) - Method in class weka.core.CheckScheme

Sets the comma-separated list of words to use for generating strings.

setWords(String) - Method in class weka.core.TestInstances

Sets the comma-separated list of words to use for generating strings.

setWordSeparators(String) - Method in class weka.core.CheckScheme

sets the word separators (chars) to use for assembling strings.

setWordSeparators(String) - Method in class weka.core.TestInstances

sets the word separators (chars) to use for assembling strings.

setWordsToKeep(int) - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.

setWordwrap(boolean) - Method in class weka.gui.LogWindow

toggles the wordwrap
override wordwrap from: http://forum.java.sun.com/thread.jspa?threadID=498535&messageID=2356174

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Associator

Sets the algorithm (associator) for this bean

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Classifier

Sets the algorithm (classifier) for this bean

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Clusterer

Sets the algorithm (clusterer) for this bean

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Filter

Set the filter to be wrapped by this bean

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Loader

Set the loader

setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Saver

Set the saver

setWrappedAlgorithm(Object) - Method in interface weka.gui.beans.WekaWrapper

Set the algorithm.

setWrappedRules(AssociationRules) - Method in class weka.associations.FilteredAssociationRules

Set the wrapped AssociationRules object to use.

setX(double) - Method in class weka.classifiers.functions.neural.NeuralConnection

setX(int) - Method in class weka.gui.beans.BeanInstance

Sets the x coordinate of this bean

setX(int) - Method in class weka.gui.visualize.AttributePanel

shows which bar is the current x attribute.

setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the x attribute index

setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the x axis fixed dimension

setXCoordinates(XCoordinates) - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Sets the value of the xCoordinates property.

setXCoordinates(XCoordinates) - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Sets the value of the xCoordinates property.

setXindex(int) - Method in class weka.gui.visualize.Plot2D

Set the index of the attribute to go on the x axis

setXindex(int) - Method in class weka.gui.visualize.PlotData2D

Set the x index of the data.

setXIndex(int) - Method in class weka.gui.visualize.VisualizePanel

Set the index of the attribute for the x axis

setXLabelFreq(int) - Method in class weka.gui.beans.StripChart

Set the frequency for printing x label values

setXML(Reader) - Method in class weka.core.xml.XMLInstances

reads the XML structure from the given reader

setXORMode(Color) - Method in class weka.gui.visualize.PostscriptGraphics

Not implemented

setXval(boolean) - Method in class weka.attributeSelection.AttributeSelection

do a cross validation

setXY(int, int) - Method in class weka.gui.beans.BeanInstance

Set the x and y coordinates of this bean

setY(double) - Method in class weka.classifiers.functions.neural.NeuralConnection

setY(int) - Method in class weka.gui.beans.BeanInstance

Sets the y coordinate of this bean

setY(int) - Method in class weka.gui.visualize.AttributePanel

shows which bar is the current y attribute.

setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Set the y attribute index

setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

Set the y axis fixed dimension

setYCoordinates(YCoordinates) - Method in class weka.core.pmml.jaxbbindings.LiftGraph

Sets the value of the yCoordinates property.

setYCoordinates(YCoordinates) - Method in class weka.core.pmml.jaxbbindings.ROCGraph

Sets the value of the yCoordinates property.

setYindex(int) - Method in class weka.gui.visualize.Plot2D

Set the index of the attribute to go on the y axis

setYindex(int) - Method in class weka.gui.visualize.PlotData2D

Set the y index of the data

setYIndex(int) - Method in class weka.gui.visualize.VisualizePanel

Set the index of the attribute for the y axis

setZeroThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.VerificationField

Sets the value of the zeroThreshold property.

setZMax(double) - Method in class weka.classifiers.meta.LogitBoost

Set the Z max threshold on the responses

setZoomSetting(int, int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective

SEVERE - Static variable in class weka.core.Debug

the log level Severe

SFEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation

Returns the total SF, which is the null model entropy minus the scheme entropy.

SFEntropyGain() - Method in class weka.classifiers.Evaluation

Returns the total SF, which is the null model entropy minus the scheme entropy.

SFMeanEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation

Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.

SFMeanEntropyGain() - Method in class weka.classifiers.Evaluation

Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.

SFMeanPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation

Returns the entropy per instance for the null model.

SFMeanPriorEntropy() - Method in class weka.classifiers.Evaluation

Returns the entropy per instance for the null model.

SFMeanSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation

Returns the entropy per instance for the scheme.

SFMeanSchemeEntropy() - Method in class weka.classifiers.Evaluation

Returns the entropy per instance for the scheme.

SFPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation

Returns the total entropy for the null model.

SFPriorEntropy() - Method in class weka.classifiers.Evaluation

Returns the total entropy for the null model.

SFSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation

Returns the total entropy for the scheme.

SFSchemeEntropy() - Method in class weka.classifiers.Evaluation

Returns the total entropy for the scheme.

SGD - Class in weka.classifiers.functions

Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression, squared loss, Huber loss and epsilon-insensitive loss linear regression).

SGD() - Constructor for class weka.classifiers.functions.SGD

SGDText - Class in weka.classifiers.functions

Implements stochastic gradient descent for learning a linear binary class SVM or binary class logistic regression on text data.

SGDText() - Constructor for class weka.classifiers.functions.SGDText

SGDText.Count - Class in weka.classifiers.functions

SGDText.Count(double) - Constructor for class weka.classifiers.functions.SGDText.Count

ShadowBorder - Class in weka.gui.beans

ShadowBorder() - Constructor for class weka.gui.beans.ShadowBorder

Constructor.

ShadowBorder(int) - Constructor for class weka.gui.beans.ShadowBorder

Constructor.

ShadowBorder(int, Color) - Constructor for class weka.gui.beans.ShadowBorder

Constructor.

shear(double, double) - Method in class weka.gui.visualize.PostscriptGraphics

shift(int, int, Instance) - Method in class weka.classifiers.trees.j48.Distribution

Shifts given instance from one bag to another one.

shift(int, int) - Method in class weka.core.matrix.IntVector

Shifts an element to another position.

shiftBeans(BeanInstance, boolean) - Method in class weka.gui.beans.MetaBean

Move coords of all inputs and outputs of this meta bean to the coords of the supplied BeanInstance.

shiftRange(int, int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution

Shifts all instances in given range from one bag to another one.

shiftToEnd(int) - Method in class weka.core.matrix.IntVector

Shifts an element to the end of the vector.

SHORT - Static variable in class weka.experiment.DatabaseUtils

Type mapping for SHORT used for reading experiment results.

show(Component, int, int) - Method in class weka.gui.GenericObjectEditor.JTreePopupMenu

Displays the menu, making sure it will fit on the screen.

showAttributes() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

displays all the attributes, returns the selected item or NULL if canceled

showAverageTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

showChart() - Method in class weka.gui.beans.StripChart

Popup the chart panel

showDialog(Component, String) - Method in class weka.gui.ConverterFileChooser

Pops a custom file chooser dialog with a custom approve button.

showDialog() - Method in class weka.gui.experiment.OutputFormatDialog

Pops up the modal dialog and waits for cancel or a selection.

showDialog() - Method in class weka.gui.ListSelectorDialog

Pops up the modal dialog and waits for cancel or a selection.

showDialog() - Method in class weka.gui.PropertySelectorDialog

Pops up the modal dialog and waits for cancel or a selection.

showDialog() - Method in class weka.gui.ViewerDialog

Pops up the modal dialog and waits for Cancel or OK.

showDialog(Instances) - Method in class weka.gui.ViewerDialog

Pops up the modal dialog and waits for Cancel or OK.

showExplorer(String) - Method in class weka.gui.GUIChooser

showHistory() - Method in class weka.gui.sql.ConnectionPanel

displays the query history.

showHistory() - Method in class weka.gui.sql.QueryPanel

displays the query history.

showInputBox(Component, String, String, Object) - Static method in class weka.gui.ComponentHelper

pops up an input dialog

showKnowledgeFlow(String) - Method in class weka.gui.GUIChooser

showMemoryIsLow() - Method in class weka.core.Memory

Prints a warning message if memoryIsLow (and if GUI is present a dialog).

showMessageBox(Component, String, String, int, int) - Static method in class weka.gui.ComponentHelper

displays a message box with the given title, message, buttons and icon ant the dimension.

showOpenDialog(Component) - Method in class weka.gui.ConverterFileChooser

Pops up an "Open File" file chooser dialog.

showOutOfMemory() - Method in class weka.core.Memory

prints an error message if OutOfMemory (and if GUI is present a dialog), otherwise nothing happens.

showPanel(ScriptingPanel, String[]) - Static method in class weka.gui.scripting.ScriptingPanel

Displays the panel in a frame.

showPanel(ScriptingPanel, String[], int, int) - Static method in class weka.gui.scripting.ScriptingPanel

Displays the panel in a frame.

showPopup() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog

if a JPopupMenu is set, it is displayed again.

showProperties() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

displays some properties of the instances

showPropertyDialog() - Method in class weka.gui.PropertyPanel

Displays the property edit dialog for the panel.

showResults() - Method in class weka.gui.beans.GraphViewer

Popup a result list from which the user can select a graph to view

showResults() - Method in class weka.gui.beans.TextViewer

Popup a component to display the selected text

showSaveDialog(Component) - Method in class weka.gui.ConverterFileChooser

Pops up an "Save File" file chooser dialog.

showStdDevTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

showTree() - Method in class weka.gui.HierarchyPropertyParser

Show the whole tree in text format

showValues() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

displays all the distinct values for an attribute

showWindow(Container) - Method in class weka.gui.Main

brings child frame to the top.

showWindow(Class<?>) - Method in class weka.gui.Main

brings the first frame to the top that is of the specified window class.

shrinkageTipText() - Method in class weka.classifiers.meta.AdditiveRegression

Returns the tip text for this property

shrinkageTipText() - Method in class weka.classifiers.meta.LogitBoost

Returns the tip text for this property

sigLevel - Variable in class weka.experiment.PairedStats

The significance level for comparisons

sigmaTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval

Returns the tip text for this property

sigmaTipText() - Method in class weka.classifiers.functions.supportVector.Puk

Returns the tip text for this property

SigmoidKernelType - Class in weka.core.pmml.jaxbbindings

Java class for SigmoidKernelType element declaration.

SigmoidKernelType() - Constructor for class weka.core.pmml.jaxbbindings.SigmoidKernelType

SigmoidUnit - Class in weka.classifiers.functions.neural

This can be used by the neuralnode to perform all it's computations (as a sigmoid unit).

SigmoidUnit() - Constructor for class weka.classifiers.functions.neural.SigmoidUnit

sign() - Method in class weka.core.matrix.DoubleVector

Returns the signs of all elements in terms of -1, 0 and +1.

SIGNIFICANCE_LOSS - Static variable in class weka.experiment.ResultMatrix

loss.

SIGNIFICANCE_TIE - Static variable in class weka.experiment.ResultMatrix

tie.

SIGNIFICANCE_WIN - Static variable in class weka.experiment.ResultMatrix

win.

significanceLevelTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

significanceLevelTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues

Returns the tip text for this property

significanceWidthTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

SimpleBatchFilter - Class in weka.filters

This filter is a superclass for simple batch filters.

SimpleBatchFilter() - Constructor for class weka.filters.SimpleBatchFilter

SimpleCLI - Class in weka.gui

Creates a very simple command line for invoking the main method of classes.

SimpleCLI() - Constructor for class weka.gui.SimpleCLI

Constructor.

SimpleCLIPanel - Class in weka.gui

Creates a very simple command line for invoking the main method of classes.

SimpleCLIPanel() - Constructor for class weka.gui.SimpleCLIPanel

SimpleCLIPanel.CommandlineCompletion - Class in weka.gui

A class for commandline completion of classnames.

SimpleCLIPanel.CommandlineCompletion() - Constructor for class weka.gui.SimpleCLIPanel.CommandlineCompletion

default constructor.

SimpleDateFormatEditor - Class in weka.gui

Class for editing SimpleDateFormat strings.

SimpleDateFormatEditor() - Constructor for class weka.gui.SimpleDateFormatEditor

Constructs a new SimpleDateFormatEditor.

SimpleEstimator - Class in weka.classifiers.bayes.net.estimate

SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned.

SimpleEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.SimpleEstimator

SimpleFilter - Class in weka.filters

This filter contains common behavior of the SimpleBatchFilter and the SimpleStreamFilter.

SimpleFilter() - Constructor for class weka.filters.SimpleFilter

SimpleKMeans - Class in weka.clusterers

Cluster data using the k means algorithm.

SimpleKMeans() - Constructor for class weka.clusterers.SimpleKMeans

the default constructor.

SimpleLinearRegression - Class in weka.classifiers.functions

Learns a simple linear regression model.

SimpleLinearRegression() - Constructor for class weka.classifiers.functions.SimpleLinearRegression

Default constructor.

SimpleLinearRegression(Instances, int, double, double) - Constructor for class weka.classifiers.functions.SimpleLinearRegression

Construct a simple linear regression model based on the given info.

SimpleLinearRegression - Class in weka.classifiers.trees.lmt

Stripped down version of SimpleLinearRegression.

SimpleLinearRegression() - Constructor for class weka.classifiers.trees.lmt.SimpleLinearRegression

Default constructor.

SimpleLinearRegression(int, double, double) - Constructor for class weka.classifiers.trees.lmt.SimpleLinearRegression

Construct a simple linear regression model based on the given info.

SimpleLogistic - Class in weka.classifiers.functions

Classifier for building linear logistic regression models.

SimpleLogistic() - Constructor for class weka.classifiers.functions.SimpleLogistic

Constructor for creating SimpleLogistic object with standard options.

SimpleLogistic(int, boolean, boolean) - Constructor for class weka.classifiers.functions.SimpleLogistic

Constructor for creating SimpleLogistic object.

SimpleMatching - Class in weka.core.pmml.jaxbbindings

Java class for simpleMatching element declaration.

SimpleMatching() - Constructor for class weka.core.pmml.jaxbbindings.SimpleMatching

SimplePredicate - Class in weka.core.pmml.jaxbbindings

Java class for SimplePredicate element declaration.

SimplePredicate() - Constructor for class weka.core.pmml.jaxbbindings.SimplePredicate

SimpleRule - Class in weka.core.pmml.jaxbbindings

Java class for SimpleRule element declaration.

SimpleRule() - Constructor for class weka.core.pmml.jaxbbindings.SimpleRule

SimpleSetPredicate - Class in weka.core.pmml.jaxbbindings

Java class for SimpleSetPredicate element declaration.

SimpleSetPredicate() - Constructor for class weka.core.pmml.jaxbbindings.SimpleSetPredicate

SimpleSetupPanel - Class in weka.gui.experiment

This panel controls the configuration of an experiment.

SimpleSetupPanel(Experiment) - Constructor for class weka.gui.experiment.SimpleSetupPanel

Creates the setup panel with the supplied initial experiment.

SimpleSetupPanel() - Constructor for class weka.gui.experiment.SimpleSetupPanel

Creates the setup panel with no initial experiment.

SimpleStreamFilter - Class in weka.filters

This filter is a superclass for simple stream filters.

SimpleStreamFilter() - Constructor for class weka.filters.SimpleStreamFilter

SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.global

This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.

For more information see:

R.R.

SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.global.SimulatedAnnealing

SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.local

This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.

For more information see:

R.R.

SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.local.SimulatedAnnealing

SIN - Static variable in interface weka.core.mathematicalexpression.sym

SIN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

SINE - Static variable in class weka.datagenerators.clusterers.BIRCHCluster

Constant set for choice of pattern.

SingleAssociatorEnhancer - Class in weka.associations

Abstract utility class for handling settings common to meta associators that use a single base associator.

SingleAssociatorEnhancer() - Constructor for class weka.associations.SingleAssociatorEnhancer

SingleClassifierEnhancer - Class in weka.classifiers

Abstract utility class for handling settings common to meta classifiers that use a single base learner.

SingleClassifierEnhancer() - Constructor for class weka.classifiers.SingleClassifierEnhancer

SingleClustererEnhancer - Class in weka.clusterers

Meta-clusterer for enhancing a base clusterer.

SingleClustererEnhancer() - Constructor for class weka.clusterers.SingleClustererEnhancer

SingleIndex - Class in weka.core

Class representing a single cardinal number.

SingleIndex() - Constructor for class weka.core.SingleIndex

Default constructor.

SingleIndex(String) - Constructor for class weka.core.SingleIndex

Constructor to set initial index.

singletons(Instances, boolean) - Static method in class weka.associations.AprioriItemSet

Converts the header info of the given set of instances into a set of item sets (singletons).

singletons(Instances) - Static method in class weka.associations.ItemSet

Converts the header info of the given set of instances into a set of item sets (singletons).

singletons(Instances, Instances) - Static method in class weka.associations.LabeledItemSet

Converts the header info of the given set of instances into a set of item sets (singletons).

SINGULAR_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants

SINGULAR_DUMMY node - node with only one outgoing edge i.e.

SingularValueDecomposition - Class in weka.core.matrix

Singular Value Decomposition.

SingularValueDecomposition(Matrix) - Constructor for class weka.core.matrix.SingularValueDecomposition

Construct the singular value decomposition

size() - Method in class weka.classifiers.CostMatrix

The number of rows (and columns)

size() - Method in class weka.classifiers.evaluation.ConfusionMatrix

Gets the number of classes.

size() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Returns the number of keys in this hashtable.

size() - Method in class weka.classifiers.rules.JRip.RipperRule

the number of antecedents of the rule

size() - Method in class weka.classifiers.rules.Rule

The size of the rule.

size() - Method in class weka.core.Instances

Returns the number of instances in the dataset.

size() - Method in class weka.core.matrix.DoubleVector

Gets the size of the vector.

size() - Method in class weka.core.matrix.IntVector

Gets the size of the vector.

size() - Method in class weka.core.PropertyPath.Path

returns the number of path elements of this structure

size() - Method in class weka.core.Queue

Gets queue's size.

size() - Method in class weka.core.Tee

returns the number of streams currently in the list.

size() - Method in class weka.core.Trie

Returns the number of elements in this collection.

size() - Method in class weka.core.Trie.TrieNode

returns the number of stored strings, i.e., leaves

size() - Method in class weka.core.xml.MethodHandler

returns the number of currently stored Methods

size() - Method in class weka.gui.GenericObjectEditorHistory

Returns the number of entries in the history.

sizeOfPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation

Gets the average size of the predicted regions, relative to the range of the target in the training data, at the confidence level specified when evaluation was performed.

sizeOfPredictedRegions() - Method in class weka.classifiers.Evaluation

Gets the average size of the predicted regions, relative to the range of the target in the training data, at the confidence level specified when evaluation was performed.

skipIdenticalTipText() - Method in class weka.core.neighboursearch.LinearNNSearch

Returns the tip text for this property.

SlidingMidPointOfWidestSide - Class in weka.core.neighboursearch.kdtrees

The class that splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.

SlidingMidPointOfWidestSide() - Constructor for class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

sm(double, double) - Static method in class weka.core.Utils

Tests if a is smaller than b.

SMALL - Static variable in class weka.core.Utils

The small deviation allowed in double comparisons.

SMO - Class in weka.classifiers.functions

Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.

This implementation globally replaces all missing values and transforms nominal attributes into binary ones.

SMO() - Constructor for class weka.classifiers.functions.SMO

SMO.BinarySMO - Class in weka.classifiers.functions

Class for building a binary support vector machine.

SMO.BinarySMO() - Constructor for class weka.classifiers.functions.SMO.BinarySMO

SMOreg - Class in weka.classifiers.functions

SMOreg implements the support vector machine for regression.

SMOreg() - Constructor for class weka.classifiers.functions.SMOreg

smOrEq(double, double) - Static method in class weka.core.Utils

Tests if a is smaller or equal to b.

SMOset - Class in weka.classifiers.functions.supportVector

Stores a set of integer of a given size.

SMOset(int) - Constructor for class weka.classifiers.functions.supportVector.SMOset

Creates a new set of the given size.

SNAPSHOT - Static variable in class weka.core.Version

True if snapshot

SnowballStemmer - Class in weka.core.stemmers

A wrapper class for the Snowball stemmers.

SnowballStemmer() - Constructor for class weka.core.stemmers.SnowballStemmer

initializes the stemmer ("porter").

SnowballStemmer(String) - Constructor for class weka.core.stemmers.SnowballStemmer

initializes the stemmer with the given stemmer.

solve(Matrix) - Method in class weka.core.matrix.CholeskyDecomposition

Solve A*X = B

solve(Matrix) - Method in class weka.core.matrix.LUDecomposition

Solve A*X = B

solve(Matrix) - Method in class weka.core.matrix.Matrix

Solve A*X = B

solve(Matrix) - Method in class weka.core.matrix.QRDecomposition

Least squares solution of A*X = B

solve(double[]) - Method in class weka.core.Matrix

Deprecated. Solve A*X = B using backward substitution.

solveTranspose(Matrix) - Method in class weka.core.matrix.Matrix

Solve X*A = B, which is also A'*X' = B'

solveTriangle(Matrix, double[], boolean, boolean[]) - Static method in class weka.core.Optimization

Solve the linear equation of TX=B where T is a triangle matrix It can be solved using back/forward substitution, with O(N^2) complexity

sort(int) - Method in class weka.core.Instances

Sorts the instances based on an attribute.

sort(Attribute) - Method in class weka.core.Instances

Sorts the instances based on an attribute.

sort() - Method in class weka.core.matrix.DoubleVector

Sorts the array in place

sort() - Method in class weka.core.matrix.IntVector

Sorts the elements in place

sort(int[]) - Static method in class weka.core.Utils

Sorts a given array of integers in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.

sort(double[]) - Static method in class weka.core.Utils

Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.

sort(int) - Method in class weka.gui.SortedTableModel

sorts the table over the given column (ascending)

sort(int, boolean) - Method in class weka.gui.SortedTableModel

sorts the table over the given column, either ascending or descending

SORT_CASEINSENSITIVE - Static variable in class weka.filters.unsupervised.attribute.SortLabels

sorts the strings case-insensitive.

SORT_CASESENSITIVE - Static variable in class weka.filters.unsupervised.attribute.SortLabels

sorts the strings case-sensitive.

sortClassesByRoot(String) - Static method in class weka.gui.GenericObjectEditor

parses the given string of classes separated by ", " and returns the a hashtable with as many entries as there are different root elements in the class names (the key is the root element).

SortedTableModel - Class in weka.gui

Represents a TableModel with sorting functionality.

SortedTableModel() - Constructor for class weka.gui.SortedTableModel

initializes with no model

SortedTableModel(TableModel) - Constructor for class weka.gui.SortedTableModel

initializes with the given model

SortedTableModel.SortContainer - Class in weka.gui

Helper class for sorting the columns.

SortedTableModel.SortContainer(Comparable<?>, int) - Constructor for class weka.gui.SortedTableModel.SortContainer

Initializes the container.

Sorter - Class in weka.gui.beans

Sorts incoming instances in ascending or descending order according to the values of user specified attributes.

Sorter() - Constructor for class weka.gui.beans.Sorter

Constructs a new Sorter

SorterBeanInfo - Class in weka.gui.beans

BeanInfo class for the Sorter step

SorterBeanInfo() - Constructor for class weka.gui.beans.SorterBeanInfo

SorterCustomizer - Class in weka.gui.beans

Customizer for the Sorter step

SorterCustomizer() - Constructor for class weka.gui.beans.SorterCustomizer

Constructor

sortInstances() - Method in class weka.gui.arffviewer.ArffPanel

sorts the instances via the currently selected column

sortInstances(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel

sorts the instances via the given attribute

sortInstances(int) - Method in class weka.gui.arffviewer.ArffTableModel

sorts the instances via the given attribute

sortInstances() - Method in class weka.gui.arffviewer.ArffViewerMainPanel

sorts the current selected attribute

SortLabels - Class in weka.filters.unsupervised.attribute

A simple filter for sorting the labels of nominal attributes.

SortLabels() - Constructor for class weka.filters.unsupervised.attribute.SortLabels

SortLabels.CaseInsensitiveComparator - Class in weka.filters.unsupervised.attribute

Represents a case-insensitive comparator for two strings.

SortLabels.CaseInsensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator

SortLabels.CaseSensitiveComparator - Class in weka.filters.unsupervised.attribute

Represents a case-sensitive comparator for two strings.

SortLabels.CaseSensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator

sortTipText() - Method in class weka.filters.unsupervised.attribute.AddValues

Returns the tip text for this property

sortTypeTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels

Returns the tip text for this property.

sortWithIndex() - Method in class weka.core.matrix.DoubleVector

Sorts the array in place with index returned

sortWithIndex(int, int, IntVector) - Method in class weka.core.matrix.DoubleVector

Sorts the array in place with index changed

sortWithNoMissingValues(double[]) - Static method in class weka.core.Utils

Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.

Sourcable - Interface in weka.classifiers

Interface for classifiers that can be converted to Java source.

Sourcable - Interface in weka.filters

Interface for filters that can be converted to Java source.

sourceClass(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split

Returns a string containing java source code equivalent to the test made at this node.

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split

Returns a string containing java source code equivalent to the test made at this node.

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit

Returns a string containing java source code equivalent to the test made at this node.

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit

Returns a string containing java source code equivalent to the test made at this node.

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit

Returns a string containing java source code equivalent to the test made at this node.

sourceExpression(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit

Method not in use

SOUTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual

spaceHorizontal(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet

space out set of nodes evenly between left and right most node in the list

spaceVertical(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet

space out set of nodes evenly between top and bottom most node in the list

SPARSE - Static variable in class weka.core.json.JSONInstances

the sparse attribute.

SPARSE1 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection

distribution type: sparse 1

SPARSE2 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection

distribution type: sparse 2

SPARSE_SEPARATOR - Static variable in class weka.core.json.JSONInstances

the separator for index/value in case of sparse instances.

SparseArray - Class in weka.core.pmml

Implementation of a sparse array.

sparseDataTipText() - Method in class weka.core.converters.DatabaseLoader

Returns the tip text for this property

sparseDataTipText() - Method in class weka.experiment.InstanceQuery

Returns the tip text for this property

sparseIndices() - Method in class weka.classifiers.functions.SMO

Returns the indices in sparse format.

SparseInstance - Class in weka.core

Class for storing an instance as a sparse vector.

SparseInstance(Instance) - Constructor for class weka.core.SparseInstance

Constructor that generates a sparse instance from the given instance.

SparseInstance(SparseInstance) - Constructor for class weka.core.SparseInstance

Constructor that copies the info from the given instance.

SparseInstance(double, double[]) - Constructor for class weka.core.SparseInstance

Constructor that generates a sparse instance from the given parameters.

SparseInstance(double, double[], int[], int) - Constructor for class weka.core.SparseInstance

Constructor that inititalizes instance variable with given values.

SparseInstance(int) - Constructor for class weka.core.SparseInstance

Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.

SparseToNonSparse - Class in weka.filters.unsupervised.instance

An instance filter that converts all incoming sparse instances into non-sparse format.

SparseToNonSparse() - Constructor for class weka.filters.unsupervised.instance.SparseToNonSparse

sparseWeights() - Method in class weka.classifiers.functions.SMO

Returns the weights in sparse format.

SpecialFunctions - Class in weka.core

Class implementing some mathematical functions.

SpecialFunctions() - Constructor for class weka.core.SpecialFunctions

sphere - Variable in class weka.classifiers.lazy.kstar.KStarWrapper

used/reused to hold the sphere size

splash(Image) - Static method in class weka.gui.SplashWindow

Open's a splash window using the specified image.

splash(URL) - Static method in class weka.gui.SplashWindow

Open's a splash window using the specified image.

SplashWindow - Class in weka.gui

A Splash window.

Split - Class in weka.classifiers.trees.ht

Base class for different split types

Split() - Constructor for class weka.classifiers.trees.ht.Split

split(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Splits the given set of instances into subsets.

split() - Method in class weka.classifiers.trees.m5.RuleNode

Finds an attribute and split point for this node

splitAtt() - Method in class weka.classifiers.trees.m5.RuleNode

Get the index of the splitting attribute for this node

splitAttr() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the attribute used in this split

splitAttr() - Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the attribute used in this split

splitAttr() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the attribute used in this split

splitAttributes() - Method in class weka.classifiers.trees.ht.Split

SplitCandidate - Class in weka.classifiers.trees.ht

Encapsulates a candidate split

SplitCandidate(Split, List<Map<String, WeightMass>>, double) - Constructor for class weka.classifiers.trees.ht.SplitCandidate

Constructor

splitConfidenceTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

SplitCriterion - Class in weka.classifiers.trees.j48

Abstract class for computing splitting criteria with respect to distributions of class values.

SplitCriterion() - Constructor for class weka.classifiers.trees.j48.SplitCriterion

splitCriterionTipText() - Method in class weka.classifiers.trees.HoeffdingTree

Returns the tip text for this property

splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit

Computes entropy for given distribution.

splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit

Computes entropy of test distribution with respect to training distribution.

splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit

This method is a straightforward implementation of the gain ratio criterion for the given distribution.

splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit

This method computes the gain ratio in the same way C4.5 does.

splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit

This method is a straightforward implementation of the information gain criterion for the given distribution.

splitCritValue(Distribution, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit

This method computes the information gain in the same way C4.5 does.

splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit

This method computes the information gain in the same way C4.5 does.

splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion

Computes result of splitting criterion for given distribution.

splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion

Computes result of splitting criterion for given training and test distributions.

splitCritValue(Distribution, Distribution, int) - Method in class weka.classifiers.trees.j48.SplitCriterion

Computes result of splitting criterion for given training and test distributions and given number of classes.

splitCritValue(Distribution, Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion

Computes result of splitting criterion for given training and test distributions and given default distribution.

splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.Antd

splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.NominalAntd

Implements the splitData function.

splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.NumericAntd

Implements the splitData function.

splitEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit

Computes entropy after splitting without considering the class values.

SplitEvaluate - Interface in weka.classifiers.trees.m5

Interface for objects that determine a split point on an attribute

SplitEvaluator - Interface in weka.experiment

Interface to objects able to generate a fixed set of results for a particular split of a dataset.

splitEvaluatorTipText() - Method in class weka.experiment.CrossValidationResultProducer

Returns the tip text for this property

splitEvaluatorTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer

Returns the tip text for this property.

splitEvaluatorTipText() - Method in class weka.experiment.RandomSplitResultProducer

Returns the tip text for this property

SplitMetric - Class in weka.classifiers.trees.ht

Base class for split metrics

SplitMetric() - Constructor for class weka.classifiers.trees.ht.SplitMetric

SplitNode - Class in weka.classifiers.trees.ht

Class for a node that splits the data in a Hoeffding tree

SplitNode(Map<String, WeightMass>, Split) - Constructor for class weka.classifiers.trees.ht.SplitNode

Construct a new SplitNode

splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.BallSplitter

Splits a node into two.

splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint

Splits a ball into two.

splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension

Splits a ball into two.

splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren

Splits a ball into two.

splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter

Splits a node into two.

splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod

Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.

splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension

Splits a node into two based on the median value of the dimension in which the points have the widest spread.

splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension

Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread.

splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide

Splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.

splitOnResidualsTipText() - Method in class weka.classifiers.trees.LMT

Returns the tip text for this property

splitOptions(String) - Static method in class weka.core.Utils

Split up a string containing options into an array of strings, one for each option.

splitPoint() - Method in class weka.classifiers.trees.j48.BinC45Split

Returns the split point (numeric attribute only).

splitPoint() - Method in class weka.classifiers.trees.j48.C45Split

Returns the split point (numeric attribute only).

splitPointTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns the tip text for this property

splitVal() - Method in class weka.classifiers.trees.m5.RuleNode

Get the split point for this node

splitValue() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the split value

splitValue() - Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the split value

splitValue() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the split value

spreadInitialCountTipText() - Method in class weka.classifiers.trees.REPTree

Returns the tip text for this property

SpreadSubsample - Class in weka.filters.supervised.instance

Produces a random subsample of a dataset.

SpreadSubsample() - Constructor for class weka.filters.supervised.instance.SpreadSubsample

sqDifference(int, double, double) - Method in class weka.core.EuclideanDistance

Returns the squared difference of two values of an attribute.

SqlViewer - Class in weka.gui.sql

Represents a little tool for querying SQL databases.

SqlViewer(JFrame) - Constructor for class weka.gui.sql.SqlViewer

initializes the SqlViewer.

SqlViewerDialog - Class in weka.gui.sql

A little dialog containing the SqlViewer.

SqlViewerDialog(JFrame) - Constructor for class weka.gui.sql.SqlViewerDialog

initializes the dialog.

SQLViewerPerspective - Class in weka.gui.beans

Simple Knowledge Flow perspective that wraps the SqlViewer class

SQLViewerPerspective() - Constructor for class weka.gui.beans.SQLViewerPerspective

Constructor

SQRT - Static variable in interface weka.core.mathematicalexpression.sym

sqrt() - Method in class weka.core.matrix.DoubleVector

Returns the square-root of all the elements in the vector

sqrt() - Method in class weka.core.matrix.Matrix

returns the square root of the matrix, i.e., X from the equation X*X = A.
Steps in the Calculation (see sqrtm in Matlab):
perform eigenvalue decomposition
[V,D]=eig(A) take the square root of all elements in D (only the ones with positive sign are considered for further computation)
S=sqrt(D) calculate the root
X=V*S/V, which can be also written as X=(V'\(V*S)')'

Note: since this method uses other high-level methods, it generates several instances of matrices.

SQRT - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

square() - Method in class weka.core.matrix.DoubleVector

Returns the squared vector

square(double) - Static method in class weka.core.matrix.Maths

Returns the square of a value

SquaredEuclidean - Class in weka.core.pmml.jaxbbindings

Java class for squaredEuclidean element declaration.

SquaredEuclidean() - Constructor for class weka.core.pmml.jaxbbindings.SquaredEuclidean

SQUAREDLOSS - Static variable in class weka.classifiers.functions.SGD

the squared loss function.

src - Variable in class weka.gui.graphvisualizer.GraphEdge

The index of source node in Nodes vector

srcLbl - Variable in class weka.gui.graphvisualizer.GraphEdge

Label of source node

stableSort(double[]) - Static method in class weka.core.Utils

Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.

Stack<T> - Class in weka.core.neighboursearch.covertrees

Class implementing a stack.

Stack() - Constructor for class weka.core.neighboursearch.covertrees.Stack

Constructor.

Stack(int) - Constructor for class weka.core.neighboursearch.covertrees.Stack

Constructor.

Stacking - Class in weka.classifiers.meta

Combines several classifiers using the stacking method.

Stacking() - Constructor for class weka.classifiers.meta.Stacking

StandardEvaluationMetric - Interface in weka.classifiers.evaluation

Primarily a marker interface for a "standard" evaluation metric - i.e.

Standardize - Class in weka.filters.unsupervised.attribute

Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).

Standardize() - Constructor for class weka.filters.unsupervised.attribute.Standardize

start() - Method in class weka.core.Debug.Clock

saves the current system time (or CPU time) in msec as start time

start() - Method in class weka.gui.beans.Loader

Start loading

start() - Method in class weka.gui.beans.MetaBean

start() - Method in interface weka.gui.beans.Startable

Start the flow running

start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Start the plotting thread

start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed

Start processing

start(String[]) - Method in class weka.gui.scripting.Script

Executes the script.

start_production() - Method in class weka.core.json.Parser

Indicates start production.

start_production() - Method in class weka.core.mathematicalexpression.Parser

Indicates start production.

start_production() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Indicates start production.

start_state() - Method in class weka.core.json.Parser

Indicates start state.

start_state() - Method in class weka.core.mathematicalexpression.Parser

Indicates start state.

start_state() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser

Indicates start state.

Startable - Interface in weka.gui.beans

Interface to something that is a start point for a flow and can be launched programatically.

startApp() - Static method in class weka.gui.beans.KnowledgeFlow

Static method that can be called from a running program to launch the KnowledgeFlow

startClock() - Method in class weka.core.Debug

starts the clock

startLoading() - Method in class weka.gui.beans.Loader

Start loading data

startPlotThread() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Starts the plotting thread.

StartSetHandler - Interface in weka.attributeSelection

Interface for search methods capable of doing something sensible given a starting set of attributes.

startSetTipText() - Method in class weka.attributeSelection.BestFirst

Returns the tip text for this property

startSetTipText() - Method in class weka.attributeSelection.GreedyStepwise

Returns the tip text for this property

startSetTipText() - Method in class weka.attributeSelection.Ranker

Returns the tip text for this property

startUpComplete() - Method in interface weka.gui.beans.StartUpListener

StartUpListener - Interface in weka.gui.beans

Interface to something that can be notified of a successful startup

stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffPanel

Invoked when the target of the listener has changed its state.

stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel

Invoked when the target of the listener has changed its state.

stateChanged(ChangeEvent) - Method in class weka.gui.LogWindow

Invoked when the target of the listener has changed its state.

stateChanged(ChangeEvent) - Method in class weka.gui.sql.ResultPanel

Invoked when the target of the listener has changed its state.

stateChanged(ChangeEvent) - Method in class weka.gui.ViewerDialog

Invoked when the target of the listener has changed its state.

statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric

True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.

Statistics - Class in weka.core

Class implementing some distributions, tests, etc.

Statistics() - Constructor for class weka.core.Statistics

Stats - Class in weka.classifiers.trees.j48

Class implementing a statistical routine needed by J48 to compute its error estimate.

Stats() - Constructor for class weka.classifiers.trees.j48.Stats

Stats - Class in weka.experiment

A class to store simple statistics

Stats() - Constructor for class weka.experiment.Stats

statusFrequencyTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Return a tip text string for this property

statusMessage(String) - Method in class weka.gui.beans.FlowRunner.SimpleLogger

statusMessage(String) - Method in class weka.gui.beans.LogPanel

Sends the supplied message to the status area.

statusMessage(String) - Method in interface weka.gui.Logger

Sends the supplied message to the status line.

statusMessage(String) - Method in class weka.gui.LogPanel

Sends the supplied message to the status line.

statusMessage(String) - Method in class weka.gui.SysErrLog

Sends the supplied message to the status line.

stdDev - Variable in class weka.experiment.Stats

The std deviation of values at the last calculateDerived() call

stdDevPrecTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

stdDevWidthTipText() - Method in class weka.experiment.ResultMatrix

Returns the tip text for this property.

stealPoints(MiddleOutConstructor.TempNode, Vector<MiddleOutConstructor.TempNode>, Vector<double[]>) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor

Removes points from old anchors that are nearer to the given new anchor and adds them to the list of points of the new anchor.

stem(String) - Method in class weka.core.stemmers.IteratedLovinsStemmer

Iterated stemming of the given word.

stem(String) - Method in class weka.core.stemmers.LovinsStemmer

Returns the stemmed version of the given word.

stem(String) - Method in class weka.core.stemmers.NullStemmer

Returns the word as it is.

stem(String) - Method in class weka.core.stemmers.SnowballStemmer

Returns the word in its stemmed form.

stem(String) - Method in interface weka.core.stemmers.Stemmer

Stems the given word and returns the stemmed version

Stemmer - Interface in weka.core.stemmers

Interface for all stemming algorithms.

stemmerTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property.

stemmerTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property.

stemmerTipText() - Method in class weka.core.stemmers.SnowballStemmer

Returns the tip text for this property.

stemmerTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

Stemming - Class in weka.core.stemmers

A helper class for using the stemmers.

Stemming() - Constructor for class weka.core.stemmers.Stemming

stemString(String) - Method in class weka.core.stemmers.LovinsStemmer

Stems everything in the given string.

STEP_FIELD_NAME - Static variable in class weka.experiment.LearningRateResultProducer

The name of the key field containing the learning rate step number

stepSizeTipText() - Method in class weka.experiment.LearningRateResultProducer

Returns the tip text for this property

stirlingFormula(double) - Static method in class weka.core.Statistics

Returns the Gamma function computed by Stirling's formula.

stop() - Method in class weka.core.Debug.Clock

saves the current system (or CPU time) in msec as stop time

STOP - Static variable in class weka.core.Trie.TrieNode

the stop character

stop() - Method in class weka.gui.beans.AbstractDataSink

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.AbstractEvaluator

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.AbstractTestSetProducer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.AbstractTrainingSetProducer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.Appender

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.Associator

Stop any associator action

stop() - Method in interface weka.gui.beans.BeanCommon

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.ClassAssigner

stop() - Method in class weka.gui.beans.Classifier

Stop any classifier action

stop() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Try and stop any action

stop() - Method in class weka.gui.beans.ClassValuePicker

stop() - Method in class weka.gui.beans.Clusterer

Stop any clusterer action

stop() - Method in class weka.gui.beans.ClustererPerformanceEvaluator

Try and stop any action

stop() - Method in class weka.gui.beans.CostBenefitAnalysis

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.CrossValidationFoldMaker

Stop any action

stop() - Method in class weka.gui.beans.DataVisualizer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.Filter

Stop all action if possible

stop() - Method in class weka.gui.beans.FlowByExpression

stop() - Method in class weka.gui.beans.ImageSaver

stop() - Method in class weka.gui.beans.ImageViewer

stop() - Method in class weka.gui.beans.IncrementalClassifierEvaluator

Stop all action

stop() - Method in class weka.gui.beans.InstanceStreamToBatchMaker

Stop any action (if possible).

stop() - Method in class weka.gui.beans.Join

Attempt to stop processing

stop() - Method in class weka.gui.beans.Loader

Stop any loading action.

stop() - Method in class weka.gui.beans.MetaBean

Stop all encapsulated beans

stop() - Method in class weka.gui.beans.ModelPerformanceChart

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.PredictionAppender

stop() - Method in class weka.gui.beans.Saver

Stops the bean

stop() - Method in class weka.gui.beans.SerializedModelSaver

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.Sorter

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.StripChart

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.SubstringLabeler

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.SubstringReplacer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.TestSetMaker

stop() - Method in class weka.gui.beans.TextSaver

stop() - Method in class weka.gui.beans.TextViewer

Stop any processing that the bean might be doing.

stop() - Method in class weka.gui.beans.TrainingSetMaker

Stop any action

stop() - Method in class weka.gui.beans.TrainTestSplitMaker

Stop processing

stop() - Method in class weka.gui.scripting.Script

Stops the execution of the script.

stopAllFlows() - Method in class weka.gui.beans.FlowRunner

stopClock(String) - Method in class weka.core.Debug

stops the clock and prints the message associated with the time, but only if the logging is enabled.

stopMonitoring() - Method in class weka.gui.MemoryUsagePanel

stops the monitoring thread.

stopPlotting() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Stop the plotting thread

stopPlotting() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Stops the plotting thread.

stopScript() - Method in class weka.gui.scripting.Script.ScriptThread

Stops the script execution.

stopThreads() - Method in class weka.core.Memory

stops all the current threads, to make a restart possible

Stopwords - Class in weka.core

Class that can test whether a given string is a stop word.

Stopwords() - Constructor for class weka.core.Stopwords

initializes the stopwords (based on Rainbow).

stopwordsTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText

Returns the tip text for this property.

stopwordsTipText() - Method in class weka.classifiers.functions.SGDText

Returns the tip text for this property.

stopwordsTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns the tip text for this property.

store(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache

Stores the specified values in the cahce table for easy retrieval.

StratifiedRemoveFolds - Class in weka.filters.supervised.instance

This filter takes a dataset and outputs a specified fold for cross validation.

StratifiedRemoveFolds() - Constructor for class weka.filters.supervised.instance.StratifiedRemoveFolds

stratify(Instances, int, Random) - Static method in class weka.classifiers.rules.RuleStats

Stratify the given data into the given number of bags based on the class values.

stratify(int) - Method in class weka.core.Instances

Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).

StreamableFilter - Interface in weka.filters

Interface for filters can work with a stream of instances.

StreamThroughput - Class in weka.gui.beans

Class for measuring throughput of an incremental Knowledge Flow step.

StreamThroughput(String) - Constructor for class weka.gui.beans.StreamThroughput

Construct a new StreamThroughput

StreamThroughput(String, String, Logger) - Constructor for class weka.gui.beans.StreamThroughput

Construct a new StreamThroughput

StreamTokenizerUtils - Class in weka.core.converters

Helper class for using stream tokenizers

StreamTokenizerUtils() - Constructor for class weka.core.converters.StreamTokenizerUtils

STRING - Static variable in class weka.core.Attribute

Constant set for attributes with string values.

STRING - Static variable in class weka.core.json.Scanner

lexical states

STRING - Static variable in interface weka.core.json.sym

STRING - Static variable in class weka.experiment.DatabaseUtils

Type mapping for STRING used for reading experiment results.

STRING - Static variable in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner

lexical states

STRING - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

stringAttributesTipText() - Method in class weka.core.converters.CSVLoader

Returns the tip text for this property.

stringFreeStructure() - Method in class weka.core.Instances

Create a copy of the structure if the data has string or relational attributes, "cleanses" string types (i.e.

StringKernel - Class in weka.classifiers.functions.supportVector

Implementation of the subsequence kernel (SSK) as described in [1] and of the subsequence kernel with lambda pruning (SSK-LP) as described in [2].

For more information, see

Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J.

StringKernel() - Constructor for class weka.classifiers.functions.supportVector.StringKernel

default constructor

StringKernel(Instances, int, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.StringKernel

creates a new StringKernel object.

StringLocator - Class in weka.core

This class locates and records the indices of String attributes, recursively in case of Relational attributes.

StringLocator(Instances) - Constructor for class weka.core.StringLocator

initializes the StringLocator with the given data

StringLocator(Instances, int, int) - Constructor for class weka.core.StringLocator

Initializes the StringLocator with the given data.

StringLocator(Instances, int[]) - Constructor for class weka.core.StringLocator

Initializes the AttributeLocator with the given data.

stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Edge

This will calculate how large a rectangle using the FontMetrics passed that the lines of the label will take up

stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Node

This will return the width and height of the rectangle that the text will fit into.

stringToLevel(String) - Static method in class weka.core.Debug.Log

turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).

stringToLevel(String) - Static method in class weka.core.Debug

turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).

StringToNominal - Class in weka.filters.unsupervised.attribute

Converts a range of string attributes (unspecified number of values) to nominal (set number of values).

StringToNominal() - Constructor for class weka.filters.unsupervised.attribute.StringToNominal

StringToWordVector - Class in weka.filters.unsupervised.attribute

Converts String attributes into a set of attributes representing word occurrence (depending on the tokenizer) information from the text contained in the strings.

StringToWordVector() - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector

Default constructor.

StringToWordVector(int) - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector

Constructor that allows specification of the target number of words in the output.

stringValue(int) - Method in class weka.core.AbstractInstance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

stringValue(Attribute) - Method in class weka.core.AbstractInstance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

stringValue(int) - Method in interface weka.core.Instance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

stringValue(Attribute) - Method in interface weka.core.Instance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

StripChart - Class in weka.gui.beans

Bean that can display a horizontally scrolling strip chart.

StripChart() - Constructor for class weka.gui.beans.StripChart

StripChartBeanInfo - Class in weka.gui.beans

Bean info class for the strip chart bean

StripChartBeanInfo() - Constructor for class weka.gui.beans.StripChartBeanInfo

StripChartCustomizer - Class in weka.gui.beans

GUI Customizer for the strip chart bean

StripChartCustomizer() - Constructor for class weka.gui.beans.StripChartCustomizer

StructureProducer - Interface in weka.gui.beans

Interface for something that can describe the structure of what is encapsulated in a named event type as an empty set of Instances (i.e.

STYLE_STDERR - Static variable in class weka.gui.LogWindow

the name of the style for stderr

STYLE_STDOUT - Static variable in class weka.gui.LogWindow

the name of the style for stdout

sub(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution

Subtracts given instance from given bag.

subFlowContains(BeanInstance) - Method in class weka.gui.beans.MetaBean

subList(int, int) - Method in class weka.core.neighboursearch.covertrees.Stack

Returns a sublist of the elements in the stack.

subpath(int) - Method in class weka.core.PropertyPath.Path

returns a subpath of the current structure, starting with the specified element index up to the end

subpath(int, int) - Method in class weka.core.PropertyPath.Path

returns a subpath of the current structure, starting with the specified element index up.

subsequenceLengthTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel

Returns the tip text for this property

SubsetByExpression - Class in weka.filters.unsupervised.instance

* Filters instances according to a user-specified expression.
*
* Grammar:
*
* boolexpr_list ::= boolexpr_list boolexpr_part | boolexpr_part;
*
* boolexpr_part ::= boolexpr:e {: parser.setResult(e); :} ;
*
* boolexpr ::= BOOLEAN
* | true
* | false
* | expr < expr
* | expr <= expr
* | expr > expr
* | expr >= expr
* | expr = expr
* | ( boolexpr )
* | not boolexpr
* | boolexpr and boolexpr
* | boolexpr or boolexpr
* | ATTRIBUTE is STRING
* | ATTRIBUTE regexp STRING
* ;
*
* expr ::= NUMBER
* | ATTRIBUTE
* | ( expr )
* | opexpr
* | funcexpr
* ;
*
* opexpr ::= expr + expr
* | expr - expr
* | expr * expr
* | expr / expr
* ;
*
* funcexpr ::= abs ( expr )
* | sqrt ( expr )
* | log ( expr )
* | exp ( expr )
* | sin ( expr )
* | cos ( expr )
* | tan ( expr )
* | rint ( expr )
* | floor ( expr )
* | pow ( expr for base , expr for exponent )
* | ceil ( expr )
* ;
*
* Notes:
* - NUMBER
* any integer or floating point number
* (but not in scientific notation!)
* - STRING
* any string surrounded by single quotes;
* the string may not contain a single quote though.
* - ATTRIBUTE
* the following placeholders are recognized for
* attribute values:
* - CLASS for the class value in case a class attribute is set.
* - ATTxyz with xyz a number from 1 to # of attributes in the
* dataset, representing the value of indexed attribute.
* - regexp
* A regular expression for pattern matching, e.g., '^id.*$'
*
* Examples:
* - extracting only mammals and birds from the 'zoo' UCI dataset:
* (CLASS is 'mammal') or (CLASS is 'bird')
* - extracting only animals with at least 2 legs from the 'zoo' UCI dataset:
* (ATT14 >= 2)
* - extracting only instances with non-missing 'wage-increase-second-year'
* from the 'labor' UCI dataset:
* not ismissing(ATT3)
*

* Valid options are:

* *

SubsetByExpression() - Constructor for class weka.filters.unsupervised.instance.SubsetByExpression

subsetDL(double, double, double) - Static method in class weka.classifiers.rules.RuleStats

Subset description length:
S(t,k,p) = -k*log2(p)-(n-k)log2(1-p) Details see Quilan: "MDL and categorical theories (Continued)",ML95

SubsetEvaluator - Interface in weka.attributeSelection

Interface for attribute subset evaluators.

SubspaceCluster - Class in weka.datagenerators.clusterers

A data generator that produces data points in hyperrectangular subspace clusters.

SubspaceCluster() - Constructor for class weka.datagenerators.clusterers.SubspaceCluster

initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly

SubspaceClusterDefinition - Class in weka.datagenerators.clusterers

A single cluster for the SubspaceCluster datagenerator

Valid options are:

SubspaceClusterDefinition() - Constructor for class weka.datagenerators.clusterers.SubspaceClusterDefinition

initializes the cluster, without a parent cluster (necessary for GOE)

SubspaceClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.clusterers.SubspaceClusterDefinition

initializes the cluster with default values

subSpaceSizeTipText() - Method in class weka.classifiers.meta.RandomSubSpace

Returns the tip text for this property

substitute(String) - Method in class weka.core.Environment

Substitute a variable names for their values in the given string.

substract(AlgVector) - Method in class weka.core.AlgVector

Returns the difference of this vector minus another.

SubstringLabeler - Class in weka.gui.beans

A bean that finds matches in string attribute values (using either substring or regular expression matches) and labels the instance (sets the value of a new attribute) according to the supplied label for the matching rule.

SubstringLabeler() - Constructor for class weka.gui.beans.SubstringLabeler

Constructor

SubstringLabelerBeanInfo - Class in weka.gui.beans

Bean info class for the substring labeler bean

SubstringLabelerBeanInfo() - Constructor for class weka.gui.beans.SubstringLabelerBeanInfo

SubstringLabelerCustomizer - Class in weka.gui.beans

Customizer class for the Substring labeler step

SubstringLabelerCustomizer() - Constructor for class weka.gui.beans.SubstringLabelerCustomizer

SubstringLabelerRules - Class in weka.gui.beans

Manages a list of match rules for labeling strings.

SubstringLabelerRules(String, String, boolean, boolean, Instances, String, Logger, Environment) - Constructor for class weka.gui.beans.SubstringLabelerRules

Constructor

SubstringLabelerRules(String, String, Instances) - Constructor for class weka.gui.beans.SubstringLabelerRules

Constructor.

SubstringLabelerRules.SubstringLabelerMatchRule - Class in weka.gui.beans

Inner class encapsulating the logic for matching

SubstringLabelerRules.SubstringLabelerMatchRule() - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Constructor

SubstringLabelerRules.SubstringLabelerMatchRule(String) - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Constructor

SubstringLabelerRules.SubstringLabelerMatchRule(String, boolean, boolean, String) - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule

Constructor

SubstringReplacer - Class in weka.gui.beans

A bean that can replace substrings in the values of string attributes.

SubstringReplacer() - Constructor for class weka.gui.beans.SubstringReplacer

Constructs a new SubstringReplacer

SubstringReplacerBeanInfo - Class in weka.gui.beans

Bean info class for the substring replacer

SubstringReplacerBeanInfo() - Constructor for class weka.gui.beans.SubstringReplacerBeanInfo

SubstringReplacerCustomizer - Class in weka.gui.beans

Customizer for the SubstringReplacer

SubstringReplacerCustomizer() - Constructor for class weka.gui.beans.SubstringReplacerCustomizer

Constructor

SubstringReplacerRules - Class in weka.gui.beans

Manages a list of match and replace rules for replacing values in string attributes

SubstringReplacerRules(String, Instances, String, Logger, Environment) - Constructor for class weka.gui.beans.SubstringReplacerRules

Constructor

SubstringReplacerRules(String, Instances) - Constructor for class weka.gui.beans.SubstringReplacerRules

Constructor.

SubstringReplacerRules.SubstringReplacerMatchRule - Class in weka.gui.beans

Inner class encapsulating the logic for matching and replacing.

SubstringReplacerRules.SubstringReplacerMatchRule() - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Constructor

SubstringReplacerRules.SubstringReplacerMatchRule(String) - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Constructor

SubstringReplacerRules.SubstringReplacerMatchRule(String, String, boolean, boolean, String) - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule

Constructor

subtract(AprioriItemSet) - Method in class weka.associations.AprioriItemSet

Subtracts an item set from another one.

subtract(Distribution) - Method in class weka.classifiers.trees.j48.Distribution

Subtracts the given distribution from this one.

subtract(double[]) - Method in class weka.core.pmml.VectorInstance

Subtract the values in the supplied array from this vector instance

subtract(VectorInstance) - Method in class weka.core.pmml.VectorInstance

Subtract the supplied VectorInstance from this one and return the result as a new VectorInstance

subtract(double, double) - Method in class weka.experiment.PairedStats

Removes an observed pair of values.

subtract(double[], double[]) - Method in class weka.experiment.PairedStats

Removes an array of observed pair of values.

subtract(double) - Method in class weka.experiment.Stats

Removes a value to the observed values (no checking is done that the value being removed was actually added).

subtract(double, double) - Method in class weka.experiment.Stats

Subtracts a value that has been seen n times from the observed values

subtreeRaisingTipText() - Method in class weka.classifiers.trees.J48

Returns the tip text for this property

subvector(int, int) - Method in class weka.core.matrix.DoubleVector

Returns a subvector.

subvector(IntVector) - Method in class weka.core.matrix.DoubleVector

Returns a subvector.

subvector(int, int) - Method in class weka.core.matrix.IntVector

Returns a subvector.

subvector(IntVector) - Method in class weka.core.matrix.IntVector

Returns a subvector as indexed by an IntVector.

sum(Map<String, WeightMass>) - Static method in class weka.classifiers.trees.ht.SplitMetric

Utility method to return the sum of instance weight in a distribution

sum() - Method in class weka.core.matrix.DoubleVector

Returns the sum of all elements in the vector.

sum(double[]) - Static method in class weka.core.Utils

Computes the sum of the elements of an array of doubles.

sum(int[]) - Static method in class weka.core.Utils

Computes the sum of the elements of an array of integers.

sum - Variable in class weka.experiment.Stats

The sum of values seen

sum2() - Method in class weka.core.matrix.DoubleVector

Returns the squared sum of all elements in the vector.

sum2(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Returns ||u-v||^2

Summarizable - Interface in weka.core

Interface to something that provides a short textual summary (as opposed to toString() which is usually a fairly complete description) of itself.

sumOfWeights() - Method in class weka.core.Instances

Computes the sum of all the instances' weights.

sumSq - Variable in class weka.experiment.Stats

The sum of values squared seen

SupervisedFilter - Interface in weka.filters

Interface for filters that make use of a class attribute.

support() - Method in class weka.associations.ItemSet

Outputs the support for an item set.

support() - Method in class weka.associations.LabeledItemSet

Outputs the support for an item set.

supports(Capabilities) - Method in class weka.core.Capabilities

Returns true if the currently set capabilities support at least all of the capabiliites of the given Capabilities object (checks only the enum!)

supportsCustomEditor() - Method in class weka.gui.beans.EnvironmentField

supportsCustomEditor() - Method in class weka.gui.CostMatrixEditor

Indicates whether the cost matrix can be edited in a GUI, which it can.

supportsCustomEditor() - Method in class weka.gui.FileEditor

Returns true because we do support a custom editor.

supportsCustomEditor() - Method in class weka.gui.GenericArrayEditor

Returns true because we do support a custom editor.

supportsCustomEditor() - Method in class weka.gui.GenericObjectEditor

Returns true because we do support a custom editor.

supportsCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor

Indicates whether the date format can be edited in a GUI, which it can.

supportsMaybe(Capabilities) - Method in class weka.core.Capabilities

Returns true if the currently set capabilities support (or have a dependency) at least all of the capabilities of the given Capabilities object (checks only the enum!)

SupportVector - Class in weka.core.pmml.jaxbbindings

Java class for SupportVector element declaration.

SupportVector() - Constructor for class weka.core.pmml.jaxbbindings.SupportVector

SupportVectorMachine - Class in weka.core.pmml.jaxbbindings

Java class for SupportVectorMachine element declaration.

SupportVectorMachine() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectorMachine

SupportVectorMachineModel - Class in weka.classifiers.pmml.consumer

Implements a PMML SupportVectorMachineModel

SupportVectorMachineModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.SupportVectorMachineModel

Construct a new SupportVectorMachineModel encapsulating the information provided in the PMML document.

SupportVectorMachineModel - Class in weka.core.pmml.jaxbbindings

Java class for SupportVectorMachineModel element declaration.

SupportVectorMachineModel() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectorMachineModel

SupportVectors - Class in weka.core.pmml.jaxbbindings

Java class for SupportVectors element declaration.

SupportVectors() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectors

SUPPRESS_PROPERTY_WARNINGS - Static variable in class weka.core.xml.XMLSerialization

List of fully qualified property names to suppress any warning messages for

suppressMappingReportTipText() - Method in class weka.classifiers.misc.InputMappedClassifier

Returns the tip text for this property

suppressOutputTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the tip text for this property.

svd() - Method in class weka.core.matrix.Matrix

Singular Value Decomposition

SVMCLASSIFICATIONMETHOD - Enum in weka.core.pmml.jaxbbindings

Java class for SVM-CLASSIFICATION-METHOD.

SVMLightLoader - Class in weka.core.converters

Reads a source that is in svm light format.

For more information about svm light see:

http://svmlight.joachims.org/

SVMLightLoader() - Constructor for class weka.core.converters.SVMLightLoader

SVMLightSaver - Class in weka.core.converters

Writes to a destination that is in svm light format.

For more information about svm light see:

http://svmlight.joachims.org/

Valid options are:

SVMLightSaver() - Constructor for class weka.core.converters.SVMLightSaver

Constructor.

SVMOutput(int, Instance) - Method in class weka.classifiers.functions.SMO.BinarySMO

Computes SVM output for given instance.

SVMOutput(Instance) - Method in class weka.classifiers.functions.supportVector.RegOptimizer

SVMREPRESENTATION - Enum in weka.core.pmml.jaxbbindings

Java class for SVM-REPRESENTATION.

swap(int, int) - Method in class weka.core.FastVector

Deprecated. Swaps two elements in the vector.

swap(int, int) - Method in class weka.core.Instances

Swaps two instances in the set.

swap(int, int) - Method in class weka.core.matrix.DoubleVector

Swaps the values stored at i and j

swap(int, int) - Method in class weka.core.matrix.IntVector

Swaps the values stored at i and j

SwapValues - Class in weka.filters.unsupervised.attribute

Swaps two values of a nominal attribute.

SwapValues() - Constructor for class weka.filters.unsupervised.attribute.SwapValues

switchSetup() - Method in class weka.gui.sql.ConnectionPanel

Lets the user select a props file for changing the database connection parameters.

switchToAdvanced(Experiment) - Method in class weka.gui.experiment.SetupModePanel

Switches to the advanced setup mode.

switchToSimple(Experiment) - Method in class weka.gui.experiment.SetupModePanel

Switches to the simple setup mode only if allowed to.

sym - Interface in weka.core.json

CUP generated interface containing symbol constants.

sym - Interface in weka.core.mathematicalexpression

CUP generated interface containing symbol constants.

sym - Interface in weka.filters.unsupervised.instance.subsetbyexpression

CUP generated interface containing symbol constants.

symmetricalUncertainty(double[][]) - Static method in class weka.core.ContingencyTables

Calculates the symmetrical uncertainty for base 2.

SymmetricalUncertAttributeEval - Class in weka.attributeSelection

SymmetricalUncertAttributeEval :

Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.

SymmetricalUncertAttributeEval() - Constructor for class weka.attributeSelection.SymmetricalUncertAttributeEval

Constructor

Sync(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader

synchronizes the node ordering of this Bayes network with those in the other network (if possible).

synopsis() - Method in class weka.core.Option

Returns the option's synopsis.

SyntaxDocument - Class in weka.gui.scripting

Highlights syntax in a DefaultStyledDocument.

SyntaxDocument(Properties) - Constructor for class weka.gui.scripting.SyntaxDocument

Initializes the document.

SyntaxDocument.ATTR_TYPE - Enum in weka.gui.scripting

The attribute type.

SysErrLog - Class in weka.gui

This Logger just sends messages to System.err.

SysErrLog() - Constructor for class weka.gui.SysErrLog

SystemInfo - Class in weka.core

This class prints some information about the system setup, like Java version, JVM settings etc.

SystemInfo() - Constructor for class weka.core.SystemInfo

initializes the object and reads the system information

T

t1TipText() - Method in class weka.clusterers.Canopy: Tip text for this property
t2TipText() - Method in class weka.clusterers.Canopy: Tip text for this property
TAB_INSTANCES - Static variable in class weka.gui.arffviewer.ArffPanel: the name of the tab for instances that were set directly
tableChanged(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTable: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
tableChanged(TableModelEvent) - Method in class weka.gui.beans.InteractiveTablePanel.InteractiveTableModelListener
tableChanged(TableModelEvent) - Method in class weka.gui.SortedTableModel: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
tableExists(String) - Method in class weka.experiment.DatabaseUtils: Checks that a given table exists.
TableLocator - Class in weka.core.pmml.jaxbbindings: Java class for TableLocator element declaration.
TableLocator() - Constructor for class weka.core.pmml.jaxbbindings.TableLocator
tableNameTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.global.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.local.TabuSearch
Tag - Class in weka.core: A Tag simply associates a numeric ID with a String description.
Tag() - Constructor for class weka.core.Tag: Creates a new default Tag
Tag(int, String) - Constructor for class weka.core.Tag: Creates a new Tag instance.
Tag(int, String, String) - Constructor for class weka.core.Tag: Creates a new Tag instance.
Tag(int, String, String, boolean) - Constructor for class weka.core.Tag
TAG_ACTUAL_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the actual_nominal tag.
TAG_ACTUAL_VALUE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the actual_numeric tag.
TAG_ATTRIBUTE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the attribute tag.
TAG_ATTRIBUTE - Static variable in class weka.core.xml.XMLInstances: the attribute element
TAG_ATTRIBUTES - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the attributes tag.
TAG_ATTRIBUTES - Static variable in class weka.core.xml.XMLInstances: the attributes element
TAG_BODY - Static variable in class weka.core.xml.XMLInstances: the body element
TAG_CLASS_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the class_label tag.
TAG_DATASET - Static variable in class weka.core.xml.XMLInstances: the root element
TAG_DISTRIBUTION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the distribution tag.
TAG_ERROR - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the error tag.
TAG_HEADER - Static variable in class weka.core.xml.XMLInstances: the header element
TAG_INSTANCE - Static variable in class weka.core.xml.XMLInstances: the instance element
TAG_INSTANCES - Static variable in class weka.core.xml.XMLInstances: the data element
TAG_LABEL - Static variable in class weka.core.xml.XMLInstances: the label element
TAG_LABELS - Static variable in class weka.core.xml.XMLInstances: the labels element
TAG_METADATA - Static variable in class weka.core.xml.XMLInstances: the meta-data element
TAG_NOTES - Static variable in class weka.core.xml.XMLInstances: the notes element
TAG_OBJECT - Static variable in class weka.core.xml.XMLSerialization: the tag for an object
TAG_OPTION - Static variable in class weka.core.xml.XMLOptions: tag for a single option.
TAG_OPTIONS - Static variable in class weka.core.xml.XMLOptions: tag for a list of options.
TAG_PREDICTED_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted_nominal tag.
TAG_PREDICTED_VALUE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted_numeric tag.
TAG_PREDICTION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the prediction tag.
TAG_PREDICTIONS - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predictions tag.
TAG_PROPERTY - Static variable in class weka.core.xml.XMLInstances: the property element
TAG_VALUE - Static variable in class weka.core.xml.XMLInstances: the value element
TAGS_ATTRIBUTETYPE - Static variable in class weka.filters.unsupervised.attribute.RemoveType: Tag allowing selection of attribute type to delete
TAGS_CLUSTERSUBTYPE - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: the tags for the cluster types
TAGS_CLUSTERTYPE - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: the tags for the cluster types
TAGS_CV_TYPE - Static variable in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: the score types
TAGS_DSTRS_TYPE - Static variable in class weka.filters.unsupervised.attribute.RandomProjection: The types of distributions that can be used for calculating the random matrix
TAGS_ESTIMATOR - Static variable in class weka.classifiers.meta.RegressionByDiscretization: The filter to apply to the training data
TAGS_EVAL - Static variable in class weka.classifiers.meta.IterativeClassifierOptimizer
TAGS_EVALUATION - Static variable in class weka.attributeSelection.WrapperSubsetEval
TAGS_EVALUATION - Static variable in class weka.classifiers.rules.DecisionTable
TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcesses: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMO: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: Specifies whether document's (instance's) word frequencies are to be normalized.
TAGS_FORMAT - Static variable in class weka.core.Debug.Clock: the output formats
TAGS_GUI - Static variable in class weka.gui.Main: GUI tags.
TAGS_INPUTORDER - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: the input order tags
TAGS_LINK_TYPE - Static variable in class weka.clusterers.HierarchicalClusterer
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.CostSensitiveClassifier: Specify possible sources of the cost matrix
TAGS_METHOD - Static variable in class weka.classifiers.meta.MultiClassClassifier: The error correction modes
TAGS_MISSING - Static variable in class weka.classifiers.lazy.KStar: Define possible missing value handling methods
TAGS_PATTERN - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: the pattern tags
TAGS_PRUNING - Static variable in class weka.classifiers.functions.supportVector.StringKernel: Pruning methods
TAGS_RULES - Static variable in class weka.classifiers.meta.Vote: combination rules
TAGS_SCORE_TYPE - Static variable in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: the score types
TAGS_SELECTION - Static variable in class weka.associations.Apriori: Metric types.
TAGS_SELECTION - Static variable in class weka.associations.DefaultAssociationRule: Tags for display in the GUI
TAGS_SELECTION - Static variable in class weka.attributeSelection.BestFirst: search directions
TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegression: Attribute selection methods
TAGS_SELECTION - Static variable in class weka.classifiers.functions.SGD: Loss functions to choose from
TAGS_SELECTION - Static variable in class weka.classifiers.functions.SGDText: Loss functions to choose from
TAGS_SELECTION - Static variable in class weka.classifiers.trees.HoeffdingTree
TAGS_SELECTION - Static variable in class weka.clusterers.SimpleKMeans: Initialization methods
TAGS_SELECTION2 - Static variable in class weka.classifiers.trees.HoeffdingTree
TAGS_SORTTYPE - Static variable in class weka.filters.unsupervised.attribute.SortLabels: Tag allowing selection of sort type.
TAGS_TYPE - Static variable in class weka.filters.unsupervised.attribute.Add: the attribute type.
TAGS_WEIGHTING - Static variable in class weka.classifiers.lazy.IBk: possible instance weighting methods.
TAN - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.

For more information see:

N.
TAN() - Constructor for class weka.classifiers.bayes.net.search.global.TAN
TAN - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.

For more information see:

N.
TAN() - Constructor for class weka.classifiers.bayes.net.search.local.TAN
TAN - Static variable in interface weka.core.mathematicalexpression.sym
TAN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
Tanimoto - Class in weka.core.pmml.jaxbbindings: Java class for tanimoto element declaration.
Tanimoto() - Constructor for class weka.core.pmml.jaxbbindings.Tanimoto
Target - Class in weka.core.pmml.jaxbbindings: Java class for Target element declaration.
Target() - Constructor for class weka.core.pmml.jaxbbindings.Target
TargetMetaInfo - Class in weka.core.pmml: Class to encapsulate information about a Target.
Targets - Class in weka.core.pmml.jaxbbindings: Java class for Targets element declaration.
Targets() - Constructor for class weka.core.pmml.jaxbbindings.Targets
TargetValue - Class in weka.core.pmml.jaxbbindings: Java class for TargetValue element declaration.
TargetValue() - Constructor for class weka.core.pmml.jaxbbindings.TargetValue
TargetValueCount - Class in weka.core.pmml.jaxbbindings: Java class for TargetValueCount element declaration.
TargetValueCount() - Constructor for class weka.core.pmml.jaxbbindings.TargetValueCount
TargetValueCounts - Class in weka.core.pmml.jaxbbindings: Java class for TargetValueCounts element declaration.
TargetValueCounts() - Constructor for class weka.core.pmml.jaxbbindings.TargetValueCounts
Task - Interface in weka.experiment: Interface to something that can be remotely executed as a task.
taskFinished() - Method in class weka.gui.LogPanel: Record a task ending
taskFinished() - Method in interface weka.gui.TaskLogger: Tells the task logger that a task has completed
taskFinished() - Method in class weka.gui.WekaTaskMonitor: Tells the panel that a task has completed
TaskLogger - Interface in weka.gui: Interface for objects that display log and display information on running tasks.
taskStarted() - Method in class weka.gui.LogPanel: Record the starting of a new task
taskStarted() - Method in interface weka.gui.TaskLogger: Tells the task logger that a new task has been started
taskStarted() - Method in class weka.gui.WekaTaskMonitor: Tells the panel that a new task has been started
TaskStatusInfo - Class in weka.experiment: A class holding information for tasks being executed on RemoteEngines.
TaskStatusInfo() - Constructor for class weka.experiment.TaskStatusInfo
tauVal(double[][]) - Static method in class weka.core.ContingencyTables: Computes Goodman and Kruskal's tau-value for a contingency table.
Taxonomy - Class in weka.core.pmml.jaxbbindings: Java class for Taxonomy element declaration.
Taxonomy() - Constructor for class weka.core.pmml.jaxbbindings.Taxonomy
TechnicalInformation - Class in weka.core: Used for paper references in the Javadoc and for BibTex generation.
TechnicalInformation(TechnicalInformation.Type) - Constructor for class weka.core.TechnicalInformation: Initializes the information with the given type
TechnicalInformation(TechnicalInformation.Type, String) - Constructor for class weka.core.TechnicalInformation: Initializes the information with the given type
TechnicalInformation.Field - Enum in weka.core: the possible fields
TechnicalInformation.Type - Enum in weka.core: the different types of information
TechnicalInformationHandler - Interface in weka.core: For classes that are based on some kind of publications.
TechnicalInformationHandlerJavadoc - Class in weka.core: Generates Javadoc comments from the TechnicalInformationHandler's data.
TechnicalInformationHandlerJavadoc() - Constructor for class weka.core.TechnicalInformationHandlerJavadoc: default constructor
Tee - Class in weka.core: This class pipelines print/println's to several PrintStreams.
Tee() - Constructor for class weka.core.Tee: initializes the object, with a default printstream.
Tee(PrintStream) - Constructor for class weka.core.Tee: initializes the object with the given default printstream, e.g., System.out.
test(Attribute) - Method in class weka.core.Capabilities: Test the given attribute, whether it can be processed by the handler, given its capabilities.
test(Attribute, boolean) - Method in class weka.core.Capabilities: Test the given attribute, whether it can be processed by the handler, given its capabilities.
test(Instances) - Method in class weka.core.Capabilities: Tests the given data, whether it can be processed by the handler, given its capabilities.
test(Instances, int, int) - Method in class weka.core.Capabilities: Tests a certain range of attributes of the given data, whether it can be processed by the handler, given its capabilities.
test(String[]) - Static method in class weka.core.Instances: Method for testing this class.
Test - Class in weka.datagenerators: Class to represent a test.
Test(int, double, Instances) - Constructor for class weka.datagenerators.Test: Constructor
Test(int, double, Instances, boolean) - Constructor for class weka.datagenerators.Test: Constructor
TEST - Static variable in class weka.gui.beans.BatchClustererEvent
testAggregation() - Static method in class weka.estimators.KernelEstimator
testAggregation() - Static method in class weka.estimators.NormalEstimator
testCapabilities(Instances, int) - Method in class weka.estimators.Estimator: Test if the estimator can handle the data.
testCV(int, int) - Method in class weka.core.Instances: Creates the test set for one fold of a cross-validation on the dataset.
TestDistributions - Class in weka.core.pmml.jaxbbindings: Java class for TestDistributions element declaration.
TestDistributions() - Constructor for class weka.core.pmml.jaxbbindings.TestDistributions
Tester - Interface in weka.experiment: Interface for different kinds of Testers in the Experimenter.
TestInstances - Class in weka.core: Generates artificial datasets for testing.
TestInstances() - Constructor for class weka.core.TestInstances: the default constructor
testsetDirTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
TestSetEvent - Class in weka.gui.beans: Event encapsulating a test set
TestSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetEvent(Object, Instances, int, int) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetEvent(Object, Instances, int, int, int, int) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetListener - Interface in weka.gui.beans: Interface to something that can accpet test set events
TestSetMaker - Class in weka.gui.beans: Bean that accepts data sets and produces test sets
TestSetMaker() - Constructor for class weka.gui.beans.TestSetMaker
TestSetMakerBeanInfo - Class in weka.gui.beans: Bean info class for the test set maker bean.
TestSetMakerBeanInfo() - Constructor for class weka.gui.beans.TestSetMakerBeanInfo
testsetPrefixTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
TestSetProducer - Interface in weka.gui.beans: Interface to something that can produce test sets
testsetSuffixTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
testWithFail(Attribute) - Method in class weka.core.Capabilities: tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
testWithFail(Attribute, boolean) - Method in class weka.core.Capabilities: tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
testWithFail(Instances, int, int) - Method in class weka.core.Capabilities: tests the given data by calling the test(Instances,int,int) method and throws an exception if the test fails.
testWithFail(Instances) - Method in class weka.core.Capabilities: tests the given data by calling the test(Instances) method and throws an exception if the test fails.
TEXT - Static variable in class weka.experiment.DatabaseUtils: Type mapping for TEXT used for reading, e.g., text blobs.
TextCorpus - Class in weka.core.pmml.jaxbbindings: Java class for TextCorpus element declaration.
TextCorpus() - Constructor for class weka.core.pmml.jaxbbindings.TextCorpus
TextDictionary - Class in weka.core.pmml.jaxbbindings: Java class for TextDictionary element declaration.
TextDictionary() - Constructor for class weka.core.pmml.jaxbbindings.TextDictionary
TextDirectoryLoader - Class in weka.core.converters: Loads all text files in a directory and uses the subdirectory names as class labels.
TextDirectoryLoader() - Constructor for class weka.core.converters.TextDirectoryLoader: default constructor
TextDocument - Class in weka.core.pmml.jaxbbindings: Java class for TextDocument element declaration.
TextDocument() - Constructor for class weka.core.pmml.jaxbbindings.TextDocument
TextEvent - Class in weka.gui.beans: Event that encapsulates some textual information
TextEvent(Object, String, String) - Constructor for class weka.gui.beans.TextEvent: Creates a new TextEvent instance.
TextListener - Interface in weka.gui.beans: Interface to something that can process a TextEvent
TextModel - Class in weka.core.pmml.jaxbbindings: Java class for TextModel element declaration.
TextModel() - Constructor for class weka.core.pmml.jaxbbindings.TextModel
TextModelNormalization - Class in weka.core.pmml.jaxbbindings: Java class for TextModelNormalization element declaration.
TextModelNormalization() - Constructor for class weka.core.pmml.jaxbbindings.TextModelNormalization
TextModelSimiliarity - Class in weka.core.pmml.jaxbbindings: Java class for TextModelSimiliarity element declaration.
TextModelSimiliarity() - Constructor for class weka.core.pmml.jaxbbindings.TextModelSimiliarity
TextSaver - Class in weka.gui.beans: Simple component to save the text carried in text events out to a file
TextSaver() - Constructor for class weka.gui.beans.TextSaver: Default constructors a new TextSaver
TextSaverBeanInfo - Class in weka.gui.beans: Bean info class for the serialized model saver bean
TextSaverBeanInfo() - Constructor for class weka.gui.beans.TextSaverBeanInfo
TextSaverCustomizer - Class in weka.gui.beans: Customizer for the TextSaver component.
TextSaverCustomizer() - Constructor for class weka.gui.beans.TextSaverCustomizer: Default Constructor
TextViewer - Class in weka.gui.beans: Bean that collects and displays pieces of text
TextViewer() - Constructor for class weka.gui.beans.TextViewer
TextViewerBeanInfo - Class in weka.gui.beans: Bean info class for the text viewer
TextViewerBeanInfo() - Constructor for class weka.gui.beans.TextViewerBeanInfo
TFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
theoryDL(int) - Method in class weka.classifiers.rules.RuleStats: The description length of the theory for a given rule.
ThreadSafe - Interface in weka.core: Interface to something that is thread safe
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.CostCurve: attribute name: Threshold
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Threshold
ThresholdCurve - Class in weka.classifiers.evaluation: Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
ThresholdCurve() - Constructor for class weka.classifiers.evaluation.ThresholdCurve
ThresholdDataEvent - Class in weka.gui.beans: Event encapsulating classifier performance data based on varying a threshold over the classifier's predicted probabilities
ThresholdDataEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.ThresholdDataEvent
ThresholdDataEvent(Object, PlotData2D, Attribute) - Constructor for class weka.gui.beans.ThresholdDataEvent
ThresholdDataListener - Interface in weka.gui.beans: Interface to something that can accept ThresholdDataEvents
thresholdTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.Ranker: Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
ThresholdVisualizePanel - Class in weka.gui.visualize: This panel is a VisualizePanel, with the added ablility to display the area under the ROC curve if an ROC curve is chosen.
ThresholdVisualizePanel() - Constructor for class weka.gui.visualize.ThresholdVisualizePanel: default constructor
TIE_STRING - Variable in class weka.experiment.ResultMatrix: tie string.
Time - Class in weka.core.pmml.jaxbbindings: Java class for Time element declaration.
Time() - Constructor for class weka.core.pmml.jaxbbindings.Time
TIME - Static variable in class weka.experiment.DatabaseUtils: Type mapping for TIME used for reading TIME columns.
TimeAnchor - Class in weka.core.pmml.jaxbbindings: Java class for TimeAnchor element declaration.
TimeAnchor() - Constructor for class weka.core.pmml.jaxbbindings.TimeAnchor
TIMEANCHOR2 - Enum in weka.core.pmml.jaxbbindings: Java class for TIME-ANCHOR.
TimeCycle - Class in weka.core.pmml.jaxbbindings: Java class for TimeCycle element declaration.
TimeCycle() - Constructor for class weka.core.pmml.jaxbbindings.TimeCycle
TimeException - Class in weka.core.pmml.jaxbbindings: Java class for TimeException element declaration.
TimeException() - Constructor for class weka.core.pmml.jaxbbindings.TimeException
TIMEEXCEPTIONTYPE - Enum in weka.core.pmml.jaxbbindings: Java class for TIME-EXCEPTION-TYPE.
TIMES - Static variable in interface weka.core.mathematicalexpression.sym
times(double) - Method in class weka.core.matrix.DoubleVector: Multiplies a scalar
times(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Multiplies another DoubleVector element by element
times(double) - Method in class weka.core.matrix.Matrix: Multiply a matrix by a scalar, C = s*A
times(Matrix) - Method in class weka.core.matrix.Matrix: Linear algebraic matrix multiplication, A * B
TIMES - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
timesEquals(double) - Method in class weka.core.matrix.DoubleVector: Multiply a vector by a scalar in place, u = s * u
timesEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Multiplies another DoubleVector element by element in place
timesEquals(double) - Method in class weka.core.matrix.Matrix: Multiply a matrix by a scalar in place, A = s*A
TimeSeries - Class in weka.core.pmml.jaxbbindings: Java class for TimeSeries element declaration.
TimeSeries() - Constructor for class weka.core.pmml.jaxbbindings.TimeSeries
TIMESERIESALGORITHM - Enum in weka.core.pmml.jaxbbindings: Java class for TIMESERIES-ALGORITHM.
TimeSeriesDelta - Class in weka.filters.unsupervised.attribute: An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
TimeSeriesDelta() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesDelta
TimeSeriesModel - Class in weka.core.pmml.jaxbbindings: Java class for TimeSeriesModel element declaration.
TimeSeriesModel() - Constructor for class weka.core.pmml.jaxbbindings.TimeSeriesModel
TimeSeriesTranslate - Class in weka.filters.unsupervised.attribute: An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute values of some previous (or future) instance.
TimeSeriesTranslate() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesTranslate
TIMESERIESUSAGE - Enum in weka.core.pmml.jaxbbindings: Java class for TIMESERIES-USAGE.
Timestamp - Class in weka.core.pmml.jaxbbindings: Java class for Timestamp element declaration.
Timestamp() - Constructor for class weka.core.pmml.jaxbbindings.Timestamp
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the result field containing the timestamp
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer: The name of the result field containing the timestamp.
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer: The name of the result field containing the timestamp
TimeValue - Class in weka.core.pmml.jaxbbindings: Java class for TimeValue element declaration.
TimeValue() - Constructor for class weka.core.pmml.jaxbbindings.TimeValue
titleUpdated(TitleUpdatedEvent) - Method in interface weka.gui.scripting.event.TitleUpdatedListener: Gets called when the title of the frame/dialog needs updating.
titleUpdated(TitleUpdatedEvent) - Method in class weka.gui.scripting.ScriptingPanel: Gets called when the title of the frame/dialog needs updating.
TitleUpdatedEvent - Class in weka.gui.scripting.event: Event that gets send in case a scripting panel updates the title.
TitleUpdatedEvent(ScriptingPanel) - Constructor for class weka.gui.scripting.event.TitleUpdatedEvent: Initializes the event.
TitleUpdatedListener - Interface in weka.gui.scripting.event: Interface for frames/dialogs that listen to changes of the title.
TO_BE_RUN - Static variable in class weka.experiment.TaskStatusInfo
toArray() - Method in class weka.core.Trie: Returns an array containing all of the elements in this collection.
toArray(T[]) - Method in class weka.core.Trie: Returns an array containing all of the elements in this collection; the runtime type of the returned array is that of the specified array.
toArray() - Method in class weka.core.xml.XMLOptions: returns the current DOM document as string array.
toArray() - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns an array containing all of the elements in this list in the correct order.
toBibTex() - Method in class weka.core.TechnicalInformation: Returns a BibTex string representing this technical information.
toClassDetailsString() - Method in class weka.classifiers.evaluation.Evaluation: Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.evaluation.Evaluation: Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString() - Method in class weka.classifiers.Evaluation: Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.Evaluation: Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toCommandLine(Object) - Static method in class weka.core.Utils: Generates a commandline of the given object.
toCommandLine() - Method in class weka.core.xml.XMLOptions: returns the given DOM document as command line.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.evaluation.Evaluation: Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.Evaluation: Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toDisplay() - Method in interface weka.core.CustomDisplayStringProvider: Returns the custom display string.
toDisplay() - Method in class weka.core.Range: Returns the custom display string.
toDisplay() - Method in class weka.core.SingleIndex: Returns the custom display string.
toDoubleArray() - Method in class weka.core.BinarySparseInstance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.DenseInstance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in interface weka.core.Instance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.SparseInstance: Returns the values of each attribute as an array of doubles.
toggleLoadStatus(List<String>) - Static method in class weka.core.WekaPackageManager: Toggle the load status of the supplied list of package names
toHeader(JSONNode) - Static method in class weka.core.json.JSONInstances: Turns a JSON object, if possible, into an Instances object (only header).
toInstances(JSONNode) - Static method in class weka.core.json.JSONInstances: Turns a JSON object, if possible, into an Instances object.
toJSON(Instances) - Static method in class weka.core.json.JSONInstances: Turns the Instances object into a JSON object.
tokenize(String) - Method in class weka.core.tokenizers.AlphabeticTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.NGramTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.Tokenizer: Sets the string to tokenize.
tokenize(Tokenizer, String[]) - Static method in class weka.core.tokenizers.Tokenizer: initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.
tokenize(String) - Method in class weka.core.tokenizers.WordTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.gui.HierarchyPropertyParser: Tokenize the given string based on the seperator and put the tokens into an array of strings
Tokenizer - Class in weka.core.tokenizers: A superclass for all tokenizer algorithms.
Tokenizer() - Constructor for class weka.core.tokenizers.Tokenizer
tokenizerTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property.
tokenizerTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property.
tokenizerTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
toleranceTipText() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns the tip text for this property
toMatlab() - Method in class weka.classifiers.CostMatrix: converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatlab() - Method in class weka.core.matrix.Matrix: converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatlab() - Method in class weka.core.Matrix: Deprecated. converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatrixString() - Method in class weka.classifiers.evaluation.Evaluation: Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.evaluation.Evaluation: Outputs the performance statistics as a classification confusion matrix.
toMatrixString() - Method in class weka.classifiers.Evaluation: Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.Evaluation: Outputs the performance statistics as a classification confusion matrix.
toMegaByte(long) - Static method in class weka.core.Memory: returns the amount of bytes as MB
toOptionList(Tag[]) - Static method in class weka.core.Tag: returns a list that can be used in the listOption methods to list all the available ID strings, e.g.: <0|1|2> or <what|ever>
toOptionSynopsis(Tag[]) - Static method in class weka.core.Tag: returns a string that can be used in the listOption methods to list all the available options, i.e., "\t\tID = Text\n" for each option
toOutput() - Method in class weka.gui.visualize.JComponentWriter: saves the current component to the currently set file.
toOutput(JComponentWriter, JComponent, File) - Static method in class weka.gui.visualize.JComponentWriter: outputs the given component with the given writer in the specified file
toOutput(JComponentWriter, JComponent, File, int, int) - Static method in class weka.gui.visualize.JComponentWriter: outputs the given component with the given writer in the specified file.
TopDownConstructor - Class in weka.core.neighboursearch.balltrees: The class implementing the TopDown construction method of ball trees.
TopDownConstructor() - Constructor for class weka.core.neighboursearch.balltrees.TopDownConstructor: Creates a new instance of TopDownConstructor.
toPMML(Instances) - Method in class weka.classifiers.functions.Logistic: Produce a PMML representation of this logistic model
toPMML(Instances, Instances, double[][], int) - Static method in class weka.classifiers.pmml.producer.LogisticProducerHelper: Produce the PMML for a Logistic classifier
toPMML(Instances) - Method in interface weka.core.pmml.PMMLProducer: Produce a PMML representation
topOfTree() - Method in class weka.classifiers.trees.m5.Rule: Returns the top of the tree.
toPrologString() - Method in class weka.datagenerators.Test: Returns the test represented by a string in Prolog notation.
toResultsString() - Method in class weka.attributeSelection.AttributeSelection: get a description of the attribute selection
toSource(String) - Method in class weka.classifiers.meta.AdaBoostM1: Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.meta.LogitBoost: Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.rules.OneR: Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.rules.ZeroR: Returns a string that describes the classifier as source.
toSource(String) - Method in interface weka.classifiers.Sourcable: Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.trees.DecisionStump: Returns the decision tree as Java source code.
toSource(String) - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns source code for the tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.J48: Returns tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.REPTree: Returns the tree as if-then statements.
toSource(String) - Method in class weka.core.Capabilities: turns the capabilities object into source code.
toSource(String, int) - Method in class weka.core.Capabilities: turns the capabilities object into source code.
toSource(String, Instances) - Method in class weka.filters.AllFilter: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in interface weka.filters.Sourcable: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Center: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Normalize: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Standardize: Returns a string that describes the filter as source.
toString() - Method in class weka.associations.Apriori: Outputs the size of all the generated sets of itemsets and the rules.
toString(Instances) - Method in class weka.associations.AprioriItemSet: Returns the contents of an item set as a string.
toString() - Method in class weka.associations.AssociatorEvaluation: returns the current result
toString() - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toString() - Method in class weka.associations.DefaultAssociationRule: Get a textual description of this rule.
toString() - Method in class weka.associations.FilteredAssociator: Output a representation of this associator
toString() - Method in class weka.associations.FPGrowth: Output the association rules.
toString() - Method in class weka.associations.Item: A string representation of this item.
toString(boolean) - Method in class weka.associations.Item: A string representation of this item, (i.e.
toString(Instances) - Method in class weka.associations.ItemSet: Returns the contents of an item set as a string.
toString(Instances, char, char) - Method in class weka.associations.ItemSet: Returns the contents of an item set as a delimited string.
toString(boolean) - Method in class weka.associations.NominalItem: A string representation of this item, (i.e.
toString(boolean) - Method in class weka.associations.NumericItem: A string representation of this item, (i.e.
toString() - Method in class weka.attributeSelection.BestFirst.Link2
toString() - Method in class weka.attributeSelection.BestFirst: returns a description of the search as a String
toString() - Method in class weka.attributeSelection.CfsSubsetEval: returns a string describing CFS
toString() - Method in class weka.attributeSelection.CorrelationAttributeEval: Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.GainRatioAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.GreedyStepwise: returns a description of the search.
toString() - Method in class weka.attributeSelection.InfoGainAttributeEval: Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.OneRAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.PrincipalComponents: Returns a description of this attribute transformer
toString() - Method in class weka.attributeSelection.Ranker: returns a description of the search as a String
toString() - Method in class weka.attributeSelection.ReliefFAttributeEval: Return a description of the ReliefF attribute evaluator.
toString() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns a string describing the wrapper
toString() - Method in class weka.classifiers.bayes.BayesNet: Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayes: Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns a textual description of this classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Returns either the net (if BIF format) or the generated instances
toString() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Display a representation of this estimator
toString() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
toString() - Method in class weka.classifiers.bayes.net.MarginCalculator
toString() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: a string representation of the algorithm
toString() - Method in class weka.classifiers.BVDecompose: Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.CostMatrix: Converts a matrix to a string.
toString() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Calls toString() with a default title.
toString(String) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Outputs the performance statistics as a classification confusion matrix.
toString() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.TwoClassStats: Returns a string containing the various performance measures for the current object
toString() - Method in class weka.classifiers.functions.GaussianProcesses: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.LinearRegression: Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.Logistic: Gets a string describing the classifier.
toString() - Method in class weka.classifiers.functions.MultilayerPerceptron
toString() - Method in class weka.classifiers.functions.SGD: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SGDText
toString() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns a description of this classifier as a string
toString() - Method in class weka.classifiers.functions.SimpleLogistic: Returns a description of the logistic model (attributes/coefficients).
toString() - Method in class weka.classifiers.functions.SMO.BinarySMO: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMO: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMOreg: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns the current result
toString() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.PolyKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.Puk: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.RBFKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.VotedPerceptron: Returns textual description of classifier.
toString() - Method in class weka.classifiers.lazy.IBk: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.KStar: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LWL: Returns a description of this classifier.
toString() - Method in class weka.classifiers.meta.AdaBoostM1: Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.AdditiveRegression: Returns textual description of the classifier.
toString() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Bagging: Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.ClassificationViaRegression: Prints the classifiers.
toString() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.CVParameterSelection: Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.FilteredClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns a string describing the classifier.
toString() - Method in class weka.classifiers.meta.LogitBoost: Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MultiClassClassifier: Prints the classifiers.
toString() - Method in class weka.classifiers.meta.MultiScheme: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.RandomCommittee: Returns description of the committee.
toString() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.RandomSubSpace: Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a description of the classifier.
toString() - Method in class weka.classifiers.meta.Stacking: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Vote: Output a representation of this classifier
toString() - Method in class weka.classifiers.misc.InputMappedClassifier
toString() - Method in class weka.classifiers.misc.SerializedClassifier: Returns a string representation of the classifier
toString() - Method in class weka.classifiers.pmml.consumer.GeneralRegression: Return a textual description of this general regression.
toString() - Method in class weka.classifiers.pmml.consumer.NeuralNetwork
toString() - Method in class weka.classifiers.pmml.consumer.Regression: Return a textual description of this Regression model.
toString() - Method in class weka.classifiers.pmml.consumer.RuleSetModel: Return a textual description of this model.
toString() - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel: Get a textual description of this SupportVectorMachineModel
toString() - Method in class weka.classifiers.pmml.consumer.TreeModel
toString() - Method in class weka.classifiers.rules.DecisionTable: Returns a description of the classifier.
toString(Instances, int) - Method in class weka.classifiers.rules.DecisionTableHashKey: Convert a hash entry to a string
toString() - Method in class weka.classifiers.rules.JRip.Antd
toString() - Method in class weka.classifiers.rules.JRip.NominalAntd: Prints this antecedent
toString() - Method in class weka.classifiers.rules.JRip.NumericAntd: Prints this antecedent
toString(Attribute) - Method in class weka.classifiers.rules.JRip.RipperRule: Prints this rule
toString() - Method in class weka.classifiers.rules.JRip: Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.OneR: Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.part.ClassifierDecList: Prints rules.
toString() - Method in class weka.classifiers.rules.part.MakeDecList: Outputs the classifier into a string.
toString() - Method in class weka.classifiers.rules.PART: Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.ZeroR: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.DecisionStump: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.HoeffdingTree: Return a textual description of the mode
toString(boolean) - Method in class weka.classifiers.trees.ht.HNode: Print a textual description of the tree
toString() - Method in class weka.classifiers.trees.j48.ClassifierTree: Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return a textual description of the node
toString() - Method in class weka.classifiers.trees.J48: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns a description of the logistic model tree (tree structure and logistic models)
toString() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns a description of the logistic model (i.e., attributes and coefficients).
toString() - Method in class weka.classifiers.trees.LMT: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.m5.Impurity: Converts an Impurity object to a string
toString() - Method in class weka.classifiers.trees.m5.M5Base: Returns a description of the classifier
toString() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Returns a textual description of this linear model
toString() - Method in class weka.classifiers.trees.m5.Rule: Return a description of the m5 tree or rule
toString() - Method in class weka.classifiers.trees.m5.RuleNode: print the linear model at this node
toString() - Method in class weka.classifiers.trees.m5.Values: Converts the stats to a string
toString(Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Converts the spliting information to string
toString() - Method in class weka.classifiers.trees.RandomForest: Outputs a description of this classifier.
toString() - Method in class weka.classifiers.trees.RandomTree: Outputs the decision tree.
toString() - Method in class weka.classifiers.trees.REPTree: Outputs the decision tree.
toString(boolean) - Method in class weka.clusterers.Canopy: Return a textual description of this clusterer
toString() - Method in class weka.clusterers.Canopy
toString() - Method in class weka.clusterers.Cobweb: Returns a description of the clusterer as a string.
toString() - Method in class weka.clusterers.EM: Outputs the generated clusters into a string.
toString() - Method in class weka.clusterers.FarthestFirst: return a string describing this clusterer
toString() - Method in class weka.clusterers.FilteredClusterer: Output a representation of this clusterer.
toString() - Method in class weka.clusterers.HierarchicalClusterer
toString() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns a description of the clusterer.
toString() - Method in class weka.clusterers.SimpleKMeans: return a string describing this clusterer.
toString() - Method in class weka.core.AbstractInstance: Returns the description of one instance.
toString(int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(int, int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(Attribute) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(Attribute, int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.AlgVector: Converts a vector to a string
toString() - Method in class weka.core.Attribute: Returns a description of this attribute in ARFF format.
toString() - Method in class weka.core.AttributeExpression
toString() - Method in class weka.core.AttributeLocator: returns a string representation of this object
toString() - Method in class weka.core.AttributeStats: Returns a human readable representation of this AttributeStats instance.
toString() - Method in class weka.core.BinarySparseInstance: Returns the description of one instance in sparse format.
toString() - Method in enum weka.core.Capabilities.Capability: returns the display string of the capability
toString() - Method in class weka.core.Capabilities: returns a string representation of the capabilities
toString() - Method in class weka.core.Debug.Clock: returns the elapsed time, getStop() - getStart(), as string
toString() - Method in class weka.core.Debug.Log: returns a string representation of the logger
toString() - Method in class weka.core.Debug.Random: returns a string representation of this number generator
toString() - Method in class weka.core.Debug.SimpleLog: returns a string representation of the logger
toString() - Method in class weka.core.Debug.Timestamp: returns the timestamp as string in the specified format
toString(int, int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(Attribute, int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(Attribute) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.Instances: Returns the dataset as a string in ARFF format.
toString(StringBuffer) - Method in class weka.core.json.JSONNode: Dumps the node structure into JSON format.
toString() - Method in class weka.core.json.JSONNode: Returns a string representation of the node.
toString() - Method in class weka.core.matrix.DoubleVector: Convert the DoubleVecor to a string
toString(int, boolean) - Method in class weka.core.matrix.DoubleVector: Convert the DoubleVecor to a string
toString() - Method in class weka.core.matrix.IntVector: Converts the IntVecor to a string
toString(int, boolean) - Method in class weka.core.matrix.IntVector: Convert the IntVecor to a string
toString() - Method in class weka.core.matrix.LinearRegression: returns the coefficients in a string representation
toString() - Method in class weka.core.matrix.Matrix: Converts a matrix to a string.
toString() - Method in class weka.core.Matrix: Deprecated. Converts a matrix to a string
toString() - Method in class weka.core.NormalizableDistance: Returns an empty string.
toString() - Method in enum weka.core.pmml.Array.ArrayType
toString() - Method in class weka.core.pmml.Array
toString() - Method in class weka.core.pmml.BuiltInArithmetic
toString(String) - Method in class weka.core.pmml.BuiltInArithmetic
toString() - Method in class weka.core.pmml.BuiltInMath
toString() - Method in class weka.core.pmml.BuiltInString
toString(String) - Method in class weka.core.pmml.Constant
toString() - Method in class weka.core.pmml.DefineFunction
toString(String) - Method in class weka.core.pmml.DefineFunction
toString() - Method in class weka.core.pmml.DerivedFieldMetaInfo
toString(String) - Method in class weka.core.pmml.Discretize
toString() - Method in class weka.core.pmml.Expression
toString(String) - Method in class weka.core.pmml.Expression
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure
toString(double, double) - Method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure
toString() - Method in class weka.core.pmml.FieldMetaInfo.Interval
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Optype
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Value.Property
toString() - Method in class weka.core.pmml.FieldMetaInfo.Value
toString(String) - Method in class weka.core.pmml.FieldRef
toString() - Method in class weka.core.pmml.Function
toString(String) - Method in class weka.core.pmml.Function
toString() - Method in class weka.core.pmml.MiningFieldMetaInfo: Return a textual representation of this MiningField.
toString() - Method in class weka.core.pmml.MiningSchema: Get a textual description of the mining schema.
toString(String) - Method in class weka.core.pmml.NormContinuous
toString(String) - Method in class weka.core.pmml.NormDiscrete
toString() - Method in class weka.core.pmml.SparseArray
toString() - Method in class weka.core.PropertyPath.Path: returns the structure again as a dot-path
toString() - Method in class weka.core.PropertyPath.PathElement: returns the element once again as string
toString() - Method in class weka.core.Queue: Produces textual description of queue.
toString() - Method in class weka.core.Range: Constructs a representation of the current range.
toString() - Method in class weka.core.SelectedTag: returns the selected tag in string representation
toString() - Method in class weka.core.SingleIndex: Constructs a representation of the current range.
toString() - Method in class weka.core.stemmers.LovinsStemmer: returns a string representation of the stemmer
toString() - Method in class weka.core.stemmers.NullStemmer: returns a string representation of the stemmer
toString() - Method in class weka.core.stemmers.SnowballStemmer: returns a string representation of the stemmer.
toString() - Method in class weka.core.Stopwords: returns the current stopwords in a string
toString() - Method in class weka.core.SystemInfo: returns a string representation of all the system properties
toString() - Method in class weka.core.Tag: returns the IDStr
toString() - Method in enum weka.core.TechnicalInformation.Field: returns the display string of the Type
toString() - Method in class weka.core.TechnicalInformation: Returns a plain-text string representing this technical information.
toString() - Method in enum weka.core.TechnicalInformation.Type: returns the display string of the Type
toString() - Method in class weka.core.Tee: returns only the classname and the number of streams.
toString() - Method in class weka.core.TestInstances: returns a string representation of the object
toString() - Method in class weka.core.Trie: returns the trie in string representation
toString() - Method in class weka.core.Trie.TrieNode: returns the node in a string representation
toString() - Method in class weka.core.Version: returns the current version as string
toString() - Method in class weka.core.xml.MethodHandler: returns the internal Hashtable (propety/class - method relationship) in a string representation
toString() - Method in class weka.core.xml.XMLDocument: returns the current DOM document as XML-string.
toString() - Method in class weka.core.xml.XMLOptions: returns the object in a string representation (as indented XML output).
toString() - Method in class weka.core.xml.XMLSerializationMethodHandler: returns the read and write method handlers as string
toString() - Method in class weka.datagenerators.ClusterDefinition: returns a string representation of the cluster
toString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Make a string from the cluster features.
toString() - Method in class weka.datagenerators.Test: Returns the test represented by a string.
toString() - Method in class weka.estimators.DDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DiscreteEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DKConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DNConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KernelEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KKConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.MahalanobisEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.NDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.NNConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.NormalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.PoissonEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns textual description of this estimator.
toString() - Method in class weka.estimators.UnivariateKernelEstimator: Returns textual description of this estimator.
toString() - Method in class weka.estimators.UnivariateNormalEstimator: Returns textual description of this estimator.
toString() - Method in class weka.experiment.AveragingResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CrossValidationResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DatabaseResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.Experiment: Gets a string representation of the experiment configuration.
toString() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.LearningRateResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.PairedStats: Returns statistics on the paired comparison.
toString() - Method in class weka.experiment.PropertyNode: Returns a string description of this property.
toString() - Method in class weka.experiment.RandomSplitResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.RegressionSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.RemoteExperiment: Overides toString in Experiment
toString() - Method in class weka.experiment.ResultMatrix: returns the matrix as a string.
toString() - Method in class weka.experiment.Stats: Returns a string summarising the stats so far.
toString() - Method in class weka.filters.Filter: Returns a description of the filter, by default only the classname.
toString() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Return a nicely formatted string for display
toString() - Method in class weka.gui.arffviewer.ArffViewer: returns only the classname
toString() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns only the classname
toString() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Return a textual description of this match rule
toString() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Return a textual description of this rule
toString() - Method in class weka.gui.GenericObjectEditor.GOETreeNode: returns a string representation of this treenode.
toString() - Method in class weka.gui.graphvisualizer.GraphEdge
toString() - Method in class weka.gui.scripting.Script: Returns the content as string.
toString() - Method in class weka.gui.SortedTableModel.SortContainer: Returns a string representation of the sort container.
toString() - Method in class weka.gui.sql.event.ConnectionEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.HistoryChangedEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the event in a string representation
toString() - Method in enum weka.Run.SchemeType
toStringHeader() - Method in class weka.experiment.ResultMatrix: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixCSV: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixHTML: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixLatex: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixPlainText: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixSignificance: returns the header of the matrix as a string.
toStringInternal() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec
toStringKey() - Method in class weka.experiment.ResultMatrix: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixCSV: returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixGnuPlot: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixHTML: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixLatex: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixPlainText: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixSignificance: returns returns a key for all the col names, for better readability if the names got cut off.
toStringMatrix() - Method in class weka.experiment.ResultMatrix: returns the matrix as a string.
toStringMatrix() - Method in class weka.experiment.ResultMatrixCSV: returns the matrix in CSV format.
toStringMatrix() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the matrix in CSV format.
toStringMatrix() - Method in class weka.experiment.ResultMatrixHTML: returns the matrix in an HTML table.
toStringMatrix() - Method in class weka.experiment.ResultMatrixLatex: returns the matrix as latex table.
toStringMatrix() - Method in class weka.experiment.ResultMatrixPlainText: returns the matrix as plain text.
toStringMatrix() - Method in class weka.experiment.ResultMatrixSignificance: returns the matrix as plain text.
toStringMaxDecimalDigits(int) - Method in class weka.core.AbstractInstance: Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.
toStringMaxDecimalDigits(int) - Method in interface weka.core.Instance: Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.
toStringMetric(int, int, int, int) - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toStringNoWeight() - Method in class weka.core.DenseInstance: Returns the description of one instance (without weight appended).
toStringNoWeight(int) - Method in class weka.core.DenseInstance: Returns the description of one instance (without weight appended).
toStringNoWeight(int) - Method in interface weka.core.Instance: Returns the description of one instance (without weight appended).
toStringNoWeight() - Method in interface weka.core.Instance: Returns the description of one instance (without weight appended).
toStringNoWeight() - Method in class weka.core.SparseInstance: Returns the description of one instance in sparse format.
toStringNoWeight(int) - Method in class weka.core.SparseInstance: Returns the description of one instance in sparse format.
toStringRanking() - Method in class weka.experiment.ResultMatrix: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixCSV: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixHTML: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixLatex: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixPlainText: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixSignificance: returns the ranking in a string representation.
toStringSummary() - Method in class weka.experiment.ResultMatrix: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixCSV: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixHTML: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixLatex: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixPlainText: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixSignificance: returns the summary as string.
toSummaryString() - Method in class weka.associations.AssociatorEvaluation: returns a summary string of the evaluation with a no title
toSummaryString(String) - Method in class weka.associations.AssociatorEvaluation: returns a summary string of the evaluation with a default title
toSummaryString() - Method in class weka.classifiers.evaluation.Evaluation: Calls toSummaryString() with no title and no complexity stats.
toSummaryString(boolean) - Method in class weka.classifiers.evaluation.Evaluation: Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.evaluation.Evaluation: Outputs the performance statistics in summary form.
toSummaryString() - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in interface weka.classifiers.evaluation.IntervalBasedEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.Evaluation: Calls toSummaryString() with no title and no complexity stats.
toSummaryString(boolean) - Method in class weka.classifiers.Evaluation: Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.Evaluation: Outputs the performance statistics in summary form.
toSummaryString() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns a summary string of the evaluation with a no title
toSummaryString(String) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns a summary string of the evaluation with a default title
toSummaryString() - Method in class weka.classifiers.meta.CVParameterSelection: A concise description of the model.
toSummaryString() - Method in class weka.classifiers.rules.PART: Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.trees.J48: Returns a superconcise version of the model
toSummaryString() - Method in class weka.core.Instances: Generates a string summarizing the set of instances.
toSummaryString() - Method in interface weka.core.Summarizable: Returns a string that summarizes the object.
total() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
total() - Method in class weka.classifiers.trees.j48.Distribution: Returns total number of (possibly fractional) instances.
TOTAL_UNIFORM - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster type: total uniform
totalCost() - Method in class weka.classifiers.evaluation.Evaluation: Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCost() - Method in class weka.classifiers.Evaluation: Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCount - Variable in class weka.core.AttributeStats: The total number of values (i.e.
totalWeight() - Method in class weka.classifiers.trees.ht.HNode: Return the total weight of instances seen at this node
toXML(int, int, int, int) - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toXML(Object) - Method in class weka.core.xml.XMLSerialization: extracts all accesible properties from the given object
toXMLBIF03() - Method in class weka.classifiers.bayes.BayesNet: Returns a description of the classifier in XML BIF 0.3 format.
toXMLBIF03() - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns network in XMLBIF format
toXMLBIF03(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: return fragment of network in XMLBIF format
toXMLBIF03() - Method in class weka.classifiers.bayes.net.MarginCalculator
TP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Positive Rate
trace() - Method in class weka.core.matrix.Matrix: Matrix trace.
trainCV(int, int) - Method in class weka.core.Instances: Creates the training set for one fold of a cross-validation on the dataset.
trainCV(int, int, Random) - Method in class weka.core.Instances: Creates the training set for one fold of a cross-validation on the dataset.
TRAINING - Static variable in class weka.gui.beans.BatchClustererEvent
TrainingInstances - Class in weka.core.pmml.jaxbbindings: Java class for TrainingInstances element declaration.
TrainingInstances() - Constructor for class weka.core.pmml.jaxbbindings.TrainingInstances
TrainingSetEvent - Class in weka.gui.beans: Event encapsulating a training set
TrainingSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetEvent(Object, Instances, int, int) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetEvent(Object, Instances, int, int, int, int) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetListener - Interface in weka.gui.beans: Interface to something that can accept and process training set events
TrainingSetMaker - Class in weka.gui.beans: Bean that accepts a data sets and produces a training set
TrainingSetMaker() - Constructor for class weka.gui.beans.TrainingSetMaker
TrainingSetMakerBeanInfo - Class in weka.gui.beans: Bean info class for the training set maker bean
TrainingSetMakerBeanInfo() - Constructor for class weka.gui.beans.TrainingSetMakerBeanInfo
TrainingSetProducer - Interface in weka.gui.beans: Interface to something that can produce a training set
trainingTimeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
trainPercentTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
trainPercentTipText() - Method in class weka.gui.beans.TrainTestSplitMaker: Tip text info for this property
TrainTestSplitMaker - Class in weka.gui.beans: Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data
TrainTestSplitMaker() - Constructor for class weka.gui.beans.TrainTestSplitMaker
TrainTestSplitMakerBeanInfo - Class in weka.gui.beans: Bean info class for the train test split maker bean
TrainTestSplitMakerBeanInfo() - Constructor for class weka.gui.beans.TrainTestSplitMakerBeanInfo
TrainTestSplitMakerCustomizer - Class in weka.gui.beans: GUI customizer for the train test split maker bean
TrainTestSplitMakerCustomizer() - Constructor for class weka.gui.beans.TrainTestSplitMakerCustomizer
transactionsMustContainTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
transform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
transformAllValuesTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
transformAllValuesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
TransformationDictionary - Class in weka.core.pmml.jaxbbindings: Java class for TransformationDictionary element declaration.
TransformationDictionary() - Constructor for class weka.core.pmml.jaxbbindings.TransformationDictionary
transformBackToOriginalTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
transformedData(Instances) - Method in interface weka.attributeSelection.AttributeTransformer: Transform the supplied data set (assumed to be the same format as the training data)
transformedData(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Gets the transformed training data.
transformedHeader() - Method in interface weka.attributeSelection.AttributeTransformer: Returns just the header for the transformed data (ie.
transformedHeader() - Method in class weka.attributeSelection.PrincipalComponents: Returns just the header for the transformed data (ie.
translate(int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Translates the origin of the graphics context to the point (x, y) in the current coordinate system.
translate(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
translateDBColumnType(String) - Method in class weka.experiment.DatabaseUtils: translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
translateDBColumnType(String) - Method in interface weka.experiment.InstanceQueryAdapter: translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
translationTipText() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the tip text for this property.
transpose() - Method in class weka.core.matrix.Matrix: Matrix transpose.
transpose() - Method in class weka.core.Matrix: Deprecated. Returns the transpose of a matrix.
Transpose - Class in weka.filters.unsupervised.attribute: Transposes the data: instances become attributes and attributes become instances.
Transpose() - Constructor for class weka.filters.unsupervised.attribute.Transpose
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute: Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".
treatMissingValuesAsZeroTipText() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns the tip text for this property
treatZeroAsMissingTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
TREE - Static variable in interface weka.core.Drawable
TreeBuild - Class in weka.gui.treevisualizer: This class will parse a dotty file and construct a tree structure from it with Edge's and Node's
TreeBuild() - Constructor for class weka.gui.treevisualizer.TreeBuild: Upon construction this will only setup the color table for quick reference of a color.
TreeDisplayEvent - Class in weka.gui.treevisualizer: An event containing the user selection from the tree display
TreeDisplayEvent(int, String) - Constructor for class weka.gui.treevisualizer.TreeDisplayEvent: Constructs an event with the specified command and what the command is applied to.
TreeDisplayListener - Interface in weka.gui.treevisualizer: Interface implemented by classes that wish to recieve user selection events from a tree displayer.
treeErrors() - Method in class weka.classifiers.trees.lmt.LMTNode: Updates the numIncorrectTree field for all nodes.
TreeModel - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML TreeModel.
TreeModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.TreeModel
TreeModel - Class in weka.core.pmml.jaxbbindings: Java class for TreeModel element declaration.
TreeModel() - Constructor for class weka.core.pmml.jaxbbindings.TreeModel
TreePerformanceStats - Class in weka.core.neighboursearch: The class that measures the performance of a tree based nearest neighbour search algorithm.
TreePerformanceStats() - Constructor for class weka.core.neighboursearch.TreePerformanceStats: Default constructor.
treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode: Recursively builds a textual description of the tree
TreeVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
TreeVisualizer - Class in weka.gui.treevisualizer: Class for displaying a Node structure in Swing.
TreeVisualizer(TreeDisplayListener, String, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer: Constructs Displayer to display a tree provided in a dot format.
TreeVisualizer(TreeDisplayListener, Node, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer: Constructs Displayer with the specified Node as the top of the tree, and uses the NodePlacer to place the Nodes.
TrendExpoSmooth - Class in weka.core.pmml.jaxbbindings: Java class for Trend_ExpoSmooth element declaration.
TrendExpoSmooth() - Constructor for class weka.core.pmml.jaxbbindings.TrendExpoSmooth
TRIANGLEDOWN_SHAPE - Static variable in class weka.gui.visualize.Plot2D
TRIANGLEUP_SHAPE - Static variable in class weka.gui.visualize.Plot2D
TRICUBE - Static variable in class weka.classifiers.lazy.LWL
Trie - Class in weka.core: A class representing a Trie data structure for strings.
Trie() - Constructor for class weka.core.Trie: initializes the data structure
Trie.TrieIterator - Class in weka.core: Represents an iterator over a trie
Trie.TrieIterator(Trie.TrieNode) - Constructor for class weka.core.Trie.TrieIterator: initializes the iterator
Trie.TrieNode - Class in weka.core: Represents a node in the trie.
Trie.TrieNode(char) - Constructor for class weka.core.Trie.TrieNode: initializes the node
Trie.TrieNode(Character) - Constructor for class weka.core.Trie.TrieNode: initializes the node
trim() - Method in class weka.gui.LogWindow: trims the JTextPane, if too big
trimTipText() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the tip text for this property
TRUE - Static variable in interface weka.core.mathematicalexpression.sym
True - Class in weka.core.pmml.jaxbbindings: Java class for True element declaration.
True() - Constructor for class weka.core.pmml.jaxbbindings.True
TRUE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
TRUE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Negatives
TRUE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Positives
trueNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true negative rate with respect to a particular class.
trueNegativeRate(int) - Method in class weka.classifiers.Evaluation: Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true positive rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.Evaluation: Calculate the true positive rate with respect to a particular class.
truncateTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
TStartTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
TStartTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
turnChecksOff() - Method in class weka.classifiers.functions.LinearRegression: Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMO: Turns off checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.LinearRegression: Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMO: Turns on checks for missing values, etc.
TwoClassStats - Class in weka.classifiers.evaluation: Encapsulates performance functions for two-class problems.
TwoClassStats(double, double, double, double) - Constructor for class weka.classifiers.evaluation.TwoClassStats: Creates the TwoClassStats with the given initial performance values.
type() - Method in class weka.core.Attribute: Returns the attribute's type as an integer.
TYPE - Static variable in class weka.core.json.JSONInstances: the type attribute.
type - Variable in class weka.gui.graphvisualizer.GraphEdge: The type of Edge
typeIsNumeric(int) - Static method in class weka.gui.sql.ResultSetHelper: returns whether the SQL type is numeric (and therefore the justification should be right).
typeName(int) - Static method in class weka.experiment.DatabaseUtils: Returns the name associated with a SQL type.
typeToClass(int) - Static method in class weka.gui.sql.ResultSetHelper: Returns the class associated with a SQL type.
typeToString(Attribute) - Static method in class weka.core.Attribute: Returns a string representation of the attribute type.
typeToString(int) - Static method in class weka.core.Attribute: Returns a string representation of the attribute type.
typeToStringShort(Attribute) - Static method in class weka.core.Attribute: Returns a short string representation of the attribute type.
typeToStringShort(int) - Static method in class weka.core.Attribute: Returns a short string representation of the attribute type.

U

uminus() - Method in class weka.core.matrix.Matrix: Unary minus
UnassignedClassException - Exception in weka.core: Exception that is raised when trying to use some data that has no class assigned to it, but a class is needed to perform the operation.
UnassignedClassException() - Constructor for exception weka.core.UnassignedClassException: Creates a new UnassignedClassException with no message.
UnassignedClassException(String) - Constructor for exception weka.core.UnassignedClassException: Creates a new UnassignedClassException.
UnassignedDatasetException - Exception in weka.core: Exception that is raised when trying to use something that has no reference to a dataset, when one is required.
UnassignedDatasetException() - Constructor for exception weka.core.UnassignedDatasetException: Creates a new UnassignedDatasetException with no message.
UnassignedDatasetException(String) - Constructor for exception weka.core.UnassignedDatasetException: Creates a new UnassignedDatasetException.
unbackQuoteChars(String) - Static method in class weka.core.Utils: The inverse operation of backQuoteChars().
unclassified() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
unclassified() - Method in class weka.classifiers.Evaluation: Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
UNCONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is not connected to any others.
undefinedDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: undefined
undo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: undo the last edit action performed on the network.
undo() - Method in interface weka.core.Undoable: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffPanel: performs an undo action
undo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffTableModel: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: undoes the last action
undo() - Method in class weka.gui.explorer.PreprocessPanel: Reverts to the last backed up version of the dataset.
Undoable - Interface in weka.core: Interface implemented by classes that support undo.
UNHANDLED_DIALOG - Static variable in class weka.gui.ConverterFileChooser: unhandled type of dialog.
UNIFORM_RANDOM - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster type: uniform/random
UniformDistribution - Class in weka.core.pmml.jaxbbindings: Java class for UniformDistribution element declaration.
UniformDistribution() - Constructor for class weka.core.pmml.jaxbbindings.UniformDistribution
uninstallPackage(String, boolean, PrintStream...) - Static method in class weka.core.WekaPackageManager: Uninstall a named package
uniqueCount - Variable in class weka.core.AttributeStats: The number of values that only appear once
UnivariateDensityEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate density estimators.
UnivariateEqualFrequencyHistogramEstimator - Class in weka.estimators: Simple histogram density estimator.
UnivariateEqualFrequencyHistogramEstimator() - Constructor for class weka.estimators.UnivariateEqualFrequencyHistogramEstimator
UnivariateIntervalEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate interval estimators.
UnivariateKernelEstimator - Class in weka.estimators: Simple weighted kernel density estimator.
UnivariateKernelEstimator() - Constructor for class weka.estimators.UnivariateKernelEstimator
UnivariateNominalMultiwaySplit - Class in weka.classifiers.trees.ht: A multiway split based on a single nominal attribute
UnivariateNominalMultiwaySplit(String) - Constructor for class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit: Constructor
UnivariateNormalEstimator - Class in weka.estimators: Simple weighted normal density estimator.
UnivariateNormalEstimator() - Constructor for class weka.estimators.UnivariateNormalEstimator
UnivariateNumericBinarySplit - Class in weka.classifiers.trees.ht: A binary split based on a single numeric attribute
UnivariateNumericBinarySplit(String, double) - Constructor for class weka.classifiers.trees.ht.UnivariateNumericBinarySplit: Constructor
UnivariateQuantileEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate quantile estimators.
UnivariateStats - Class in weka.core.pmml.jaxbbindings: Java class for UnivariateStats element declaration.
UnivariateStats() - Constructor for class weka.core.pmml.jaxbbindings.UnivariateStats
UNKNOWN_NOMINAL_VALUE - Static variable in class weka.core.pmml.MappingInfo: Index for incoming nominal values that are not defined in the mining schema.
unnormalizedKernel(char[], char[]) - Method in class weka.classifiers.functions.supportVector.StringKernel: evaluates the unnormalized kernel between s and t.
unpivoting(IntVector, int) - Method in class weka.core.matrix.DoubleVector: Returns a vector from the pivoting indices.
unprunedTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
unprunedTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
unprunedTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
unquote(String) - Static method in class weka.core.Utils: unquotes are previously quoted string (but only if necessary), i.e., it removes the single quotes around it.
UNSET - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner: unset the class attribute.
unsorted() - Method in class weka.core.matrix.DoubleVector: Returns true if vector not sorted
UnsupervisedAttributeEvaluator - Class in weka.attributeSelection: Abstract unsupervised attribute evaluator.
UnsupervisedAttributeEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedAttributeEvaluator
UnsupervisedFilter - Interface in weka.filters: Interface for filters that do not need a class attribute.
UnsupervisedSubsetEvaluator - Class in weka.attributeSelection: Abstract unsupervised attribute subset evaluator.
UnsupervisedSubsetEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedSubsetEvaluator
UnsupportedAttributeTypeException - Exception in weka.core: Exception that is raised by an object that is unable to process some of the attribute types it has been passed.
UnsupportedAttributeTypeException() - Constructor for exception weka.core.UnsupportedAttributeTypeException: Creates a new UnsupportedAttributeTypeException with no message.
UnsupportedAttributeTypeException(String) - Constructor for exception weka.core.UnsupportedAttributeTypeException: Creates a new UnsupportedAttributeTypeException.
UnsupportedClassTypeException - Exception in weka.core: Exception that is raised by an object that is unable to process the class type of the data it has been passed.
UnsupportedClassTypeException() - Constructor for exception weka.core.UnsupportedClassTypeException: Creates a new UnsupportedClassTypeException with no message.
UnsupportedClassTypeException(String) - Constructor for exception weka.core.UnsupportedClassTypeException: Creates a new UnsupportedClassTypeException.
unweightedMacroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation: Unweighted macro-averaged F-measure.
unweightedMacroFmeasure() - Method in class weka.classifiers.Evaluation: Unweighted macro-averaged F-measure.
unweightedMicroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation: Unweighted micro-averaged F-measure.
unweightedMicroFmeasure() - Method in class weka.classifiers.Evaluation: Unweighted micro-averaged F-measure.
update(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set
update(double, String, double) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Update this stat with the supplied attribute value and class value
update(double, String, double) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
update(double, String, double) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
update(Instance) - Method in interface weka.core.DistanceFunction: Update the distance function (if necessary) for the newly added instance.
update(double) - Method in class weka.core.matrix.FlexibleDecimalFormat
update(Instance) - Method in class weka.core.neighboursearch.BallTree: Adds one instance to the BallTree.
update(Instance) - Method in class weka.core.neighboursearch.CoverTree: Adds an instance to the cover tree.
update(Instance) - Method in class weka.core.neighboursearch.KDTree: Adds one instance to the KDTree.
update(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Updates the NearNeighbourSearch algorithm for the new added instance.
update(Instance) - Method in class weka.core.NormalizableDistance: Update the distance function (if necessary) for the newly added instance.
update(String) - Method in class weka.experiment.DatabaseUtils: Executes a SQL DDL query or an INSERT, DELETE or UPDATE.
update(Graphics) - Method in class weka.gui.SplashWindow: Updates the display area of the window.
UpdateableClassifier - Interface in weka.classifiers: Interface to incremental classification models that can learn using one instance at a time.
UpdateableClusterer - Interface in weka.clusterers: Interface to incremental cluster models that can learn using one instance at a time.
updateChildPropertySheet() - Method in class weka.gui.GenericObjectEditor.GOEPanel: Updates the child property sheet, and creates if needed.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.BayesNet: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayes: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.functions.SGD: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.functions.SGDText: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.lazy.IBk: Adds the supplied instance to the training set.
updateClassifier(Instance) - Method in class weka.classifiers.lazy.KStar: Adds the supplied instance to the training set
updateClassifier(Instance) - Method in class weka.classifiers.lazy.LWL: Adds the supplied instance to the training set.
updateClassifier(Instance) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.trees.HoeffdingTree: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in interface weka.classifiers.UpdateableClassifier: Updates a classifier using the given instance.
updateClusterer(Instance) - Method in class weka.clusterers.Canopy
updateClusterer(Instance) - Method in class weka.clusterers.Cobweb: Adds an instance to the clusterer.
updateClusterer(Instance) - Method in interface weka.clusterers.UpdateableClusterer: Adds an instance to the clusterer.
upDateCounter(Instance) - Method in class weka.associations.ItemSet: Updates counter of item set with respect to given transaction.
upDateCounter(Instance, Instance) - Method in class weka.associations.LabeledItemSet: Updates counter of item set with respect to given transaction.
upDateCounters(ArrayList<Object>, Instances) - Static method in class weka.associations.ItemSet: Updates counters for a set of item sets and a set of instances.
upDateCounters(ArrayList<Object>, Instances, Instances) - Static method in class weka.associations.LabeledItemSet: Updates counter of a specific item set
upDateCountersTreatZeroAsMissing(ArrayList<Object>, Instances) - Static method in class weka.associations.ItemSet: Updates counters for a set of item sets and a set of instances.
upDateCountersTreatZeroAsMissing(ArrayList<LabeledItemSet>, Instances, Instances) - Static method in class weka.associations.LabeledItemSet: Updates counter of a specific item set
updateCounterTreatZeroAsMissing(Instance) - Method in class weka.associations.ItemSet: Updates counter of item set with respect to given transaction.
upDateCounterTreatZeroAsMissing(Instance, Instance) - Method in class weka.associations.LabeledItemSet: Updates counter of item set with respect to given transaction.
updateDistribution(Instance) - Method in class weka.classifiers.trees.ht.HNode: Update the class frequency distribution with the supplied instance
updateEnd(Logger) - Method in class weka.gui.beans.StreamThroughput: Register a throughput measurement end point.
updateFinished() - Method in class weka.clusterers.Canopy
updateFinished() - Method in class weka.clusterers.Cobweb: Singals the end of the updating.
updateFinished() - Method in interface weka.clusterers.UpdateableClusterer: Signals the end of the updating.
updateFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the title of the parent frame, if one was provided
updateFromChild() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set of the child clique
updateFromParent() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set of the parent clique
updateJavadoc() - Method in class weka.core.Javadoc: generates the Javadoc and returns it applied to the source file if one was provided, otherwise an empty string.
updateNode(Instance) - Method in class weka.classifiers.trees.ht.ActiveHNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.HNode: Update the node with the supplied instance
updateNode(Instance) - Method in class weka.classifiers.trees.ht.InactiveHNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.LeafNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.NBNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.NBNodeAdaptive
updateNode(Instance) - Method in class weka.classifiers.trees.ht.SplitNode
updatePointCount(int) - Method in class weka.core.neighboursearch.PerformanceStats: adds the given number to the point count.
updatePriors(Instance) - Method in class weka.classifiers.evaluation.Evaluation: Updates the class prior probabilities or the mean respectively (when incrementally training).
updatePriors(Instance) - Method in class weka.classifiers.Evaluation: Updates the class prior probabilities or the mean respectively (when incrementally training).
updateRanges(Instance, int, double[][]) - Method in class weka.core.NormalizableDistance: Updates the minimum and maximum and width values for all the attributes based on a new instance.
updateRanges(Instance, double[][]) - Method in class weka.core.NormalizableDistance: Updates the ranges given a new instance.
updateRanges(Instance) - Method in class weka.core.NormalizableDistance: Update the ranges if a new instance comes.
updateRangesFirst(Instance, int, double[][]) - Method in class weka.core.NormalizableDistance: Used to initialize the ranges.
updateResult(String) - Method in class weka.gui.ResultHistoryPanel: Tells any component currently displaying the named result that the contents of the result text in the StringBuffer have been updated.
updateStart() - Method in class weka.gui.beans.StreamThroughput: Register a throughput measurement start point
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForConditionalDensityEstimator(ConditionalDensityEstimator, Instance, double) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates stats for conditional density estimator based on current test instance.
updateStatsForIntervalEstimator(IntervalEstimator, Instance, double) - Method in interface weka.classifiers.evaluation.IntervalBasedEvaluationMetric: Updates stats for interval estimator based on current test instance.
updateStatsForPredictor(double, Instance) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates the statistics about a predictors performance for the current test instance.
updateStatsForPredictor(double, Instance) - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Updates the statistics about a predictors performance for the current test instance.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.LinearUnit: This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in interface weka.classifiers.functions.neural.NeuralMethod: This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.SigmoidUnit: This function will calculate what the change in weights should be and also update them.
updateWidth() - Method in class weka.estimators.UnivariateKernelEstimator: Updates bandwidth: the sample standard deviation is multiplied by the total weight to the power of the given exponent.
upperBoundMinSupportTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
upperBoundMinSupportTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
upperNumericBoundIsOpen() - Method in class weka.core.Attribute: Returns whether the upper numeric bound of the attribute is open.
upperSizeTipText() - Method in class weka.experiment.LearningRateResultProducer: Returns the tip text for this property
URLSourcedLoader - Interface in weka.core.converters: Interface to a loader that can load from a http url
urlTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
urlTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
USE_DYNAMIC - Static variable in class weka.gui.GenericPropertiesCreator: name of property whether to use the dynamic approach or the old GenericObjectEditor.props file
useADTreeTipText() - Method in class weka.classifiers.bayes.BayesNet
useAICTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
useAICTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
useBetterEncodingTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useBinNumbersTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useBinNumbersTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
useConjugateGradientDescentTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useCrossValidationTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSink: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSource: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractEvaluator: Use the default images for an evaluator
useDefaultVisual() - Method in class weka.gui.beans.AbstractTestSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.Appender: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.Associator: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.AttributeSummarizer: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassAssigner
useDefaultVisual() - Method in class weka.gui.beans.Classifier: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassValuePicker
useDefaultVisual() - Method in class weka.gui.beans.Clusterer: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.CostBenefitAnalysis
useDefaultVisual() - Method in class weka.gui.beans.DataVisualizer: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.Filter: Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.FlowByExpression
useDefaultVisual() - Method in class weka.gui.beans.GraphViewer: Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.ImageSaver
useDefaultVisual() - Method in class weka.gui.beans.ImageViewer
useDefaultVisual() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.Join: Use the default visual for this step
useDefaultVisual() - Method in class weka.gui.beans.MetaBean: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ModelPerformanceChart: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.PredictionAppender: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.SerializedModelSaver: Use the default images for this bean.
useDefaultVisual() - Method in class weka.gui.beans.Sorter: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.StripChart: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.SubstringLabeler: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.SubstringReplacer: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.TextSaver
useDefaultVisual() - Method in class weka.gui.beans.TextViewer: Use the default visual appearance for this bean
useDefaultVisual() - Method in interface weka.gui.beans.Visible: Use the default visual representation
useDoubleTipText() - Method in class weka.core.converters.MatlabSaver: Returns the tip text for this property.
useDynamic() - Method in class weka.gui.GenericPropertiesCreator: gets whether the dynamic approach should be used or not
useEqualFrequencyTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
useFilter(Instances, Filter) - Static method in class weka.filters.Filter: Filters an entire set of instances through a filter and returns the new set.
useIBkTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
useKernelEstimatorTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
useKononenkoTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useLaplaceTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
useLeastValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
useLowerOrderTipText() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the tip text for this property
useMDLcorrectionTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
useMDLcorrectionTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
useMissingTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useNoPriors() - Method in class weka.classifiers.evaluation.Evaluation: disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
useNoPriors() - Method in class weka.classifiers.Evaluation: disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
useNormalizationTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
useORForMustContainListTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
usePairwiseCouplingTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
useProbTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
usePruningTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
user_init() - Method in class weka.core.json.Parser: User initialization code.
userCommand(TreeDisplayEvent) - Method in interface weka.gui.treevisualizer.TreeDisplayListener: Gets called when the user selects something, in the tree display.
userDataEvent(VisualizePanelEvent) - Method in interface weka.gui.visualize.VisualizePanelListener: This method receives an object containing the shapes, instances inside and outside these shapes and the attributes these shapes were created in.
useRelativePathTipText() - Method in class weka.core.converters.AbstractFileLoader: Tip text suitable for displaying int the GUI
useRelativePathTipText() - Method in class weka.core.converters.AbstractFileSaver: Tip text suitable for displaying int the GUI
useResamplingTipText() - Method in class weka.classifiers.meta.AdaBoostM1: Returns the tip text for this property
useResamplingTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
usernameTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
UserRequestAcceptor - Interface in weka.gui.beans: Interface to something that can accept requests from a user to perform some action
userTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
userTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
useShortIdentifiersTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
useStemmer(Stemmer, String[]) - Static method in class weka.core.stemmers.Stemming: Applies the given stemmer according to the given options.
useStopListTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
useStopListTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
useStoplistTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
useSupervisedDiscretizationTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
useTabsTipText() - Method in class weka.core.converters.MatlabSaver: Returns the tip text for this property.
useTabTipText() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns the tip text for this property.
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useUnsmoothedTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
useVariant1TipText() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns the tip text for this property
useWordFrequenciesTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
useWordFrequenciesTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
Utils - Class in weka.core: Class implementing some simple utility methods.
Utils() - Constructor for class weka.core.Utils

V

VAL_ANIMATEDICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the animatedIconPath property
VAL_ASSOCIATEDCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the associatedConnections property
VAL_BEAN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the bean property
VAL_BEANCONTEXT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the beanContext property
VAL_BLUE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the blue property
VAL_CELLS - Static variable in class weka.core.xml.XMLBasicSerialization: the matrix cells
VAL_COLOR - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the color property
VAL_CUSTOM_NAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the customName property
VAL_DATE - Static variable in class weka.core.xml.XMLInstances: the value for date
VAL_DIR - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the dir property
VAL_EVENTNAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the eventname property
VAL_FILE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the file property
VAL_FONT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the font property
VAL_GREEN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the green property
VAL_HEIGHT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the height property
VAL_HIDDEN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the hidden property
VAL_ICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the iconpath property
VAL_ID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the id property
VAL_INPUTS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the input property
VAL_INPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the input id property
VAL_KEY - Static variable in class weka.core.xml.XMLBasicSerialization: the value for a mapping-key, e.g., Maps
VAL_LOADER - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the loader property
VAL_LOCATION - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the location property
VAL_MAPPING - Static variable in class weka.core.xml.XMLBasicSerialization: the value for mapping, e.g., Maps
VAL_NAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the value property
VAL_NO - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the value "no".
VAL_NO - Static variable in class weka.core.xml.XMLDocument: the value "no".
VAL_NO - Static variable in class weka.core.xml.XMLSerialization: the value "no" for the primitive and array attribute
VAL_NOMINAL - Static variable in class weka.core.xml.XMLInstances: the value for nominal
VAL_NORMAL - Static variable in class weka.core.xml.XMLInstances: the value for normal
VAL_NUMERIC - Static variable in class weka.core.xml.XMLInstances: the value for numeric
VAL_OPTIONS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the options property
VAL_ORIGINALCOORDS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the originalCoords property
VAL_OUTPUTS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the outputs id property
VAL_OUTPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the outputs property
VAL_PREFIX - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the prefix property
VAL_RED - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the red property
VAL_RELATIONAL - Static variable in class weka.core.xml.XMLInstances: the value for relational
VAL_RELATIONNAMEFORFILENAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the relationNameForFilename property (Saver)
VAL_RELATIVE_PATH - Static variable in class weka.gui.beans.xml.XMLBeans
VAL_ROOT - Static variable in class weka.core.xml.XMLSerialization: the value of the name for the root node
VAL_SAVER - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the saver property
VAL_SIZE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the size property
VAL_SOURCEID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the source property
VAL_SPARSE - Static variable in class weka.core.xml.XMLInstances: the value for sparse
VAL_STRING - Static variable in class weka.core.xml.XMLInstances: the value for string
VAL_STYLE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the style property
VAL_SUBFLOW - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the subFlow property
VAL_TARGETID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the target property
VAL_TEXT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the text property
VAL_TYPE_CLASSIFIER - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_FLAG - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_HYPHENS - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_OPTIONHANDLER - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_QUOTES - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_SINGLE - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_VALUE - Static variable in class weka.core.xml.XMLBasicSerialization: the value for mapping-value, e.g., Maps
VAL_WIDTH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the width property
VAL_X - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the x property
VAL_Y - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the y property
VAL_YES - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the value "yes".
VAL_YES - Static variable in class weka.core.xml.XMLDocument: the value "yes".
VAL_YES - Static variable in class weka.core.xml.XMLSerialization: the value "yes" for the primitive and array attribute
validateFileFormat(Tag) - Method in class weka.gui.beans.SerializedModelSaver: Validate the file format.
validationSetSizeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
validationThresholdTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
VALIDTIMESPEC - Enum in weka.core.pmml.jaxbbindings: Java class for VALID-TIME-SPEC.
value - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: scale factor or stop parameter
value(Attribute) - Method in class weka.core.AbstractInstance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.Attribute: Returns a value of a nominal or string attribute.
value(int) - Method in class weka.core.BinarySparseInstance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.DenseInstance: Returns an instance's attribute value in internal format.
value(int) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format.
value(Attribute) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array.
value() - Method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
value() - Method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.DATATYPE
value() - Method in enum weka.core.pmml.jaxbbindings.DELIMITER2
value() - Method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
value() - Method in enum weka.core.pmml.jaxbbindings.GAP
value() - Method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY
value() - Method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY
value() - Method in enum weka.core.pmml.jaxbbindings.OPTYPE
value() - Method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE
value() - Method in enum weka.core.pmml.jaxbbindings.RULEFEATURE
value() - Method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION
value() - Method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2
value() - Method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE
value() - Method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM
value() - Method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE
value() - Method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC
Value - Class in weka.core.pmml.jaxbbindings: Java class for Value element declaration.
Value() - Constructor for class weka.core.pmml.jaxbbindings.Value
Value(String) - Constructor for class weka.core.pmml.jaxbbindings.Value
value(int) - Method in class weka.core.pmml.SparseArray: Gets the value at index from the array.
value(int) - Method in class weka.core.SparseInstance: Returns an instance's attribute value in internal format.
value - Variable in class weka.experiment.PropertyNode: The current property value
valueDouble(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a double.
valueFloat(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a float.
valueIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
valueInt(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as an int.
valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.EuclideanDistance: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueOf(String) - Static method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.associations.NumericItem.Comparison: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.Capabilities.Capability: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.json.JSONNode.NodeType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.logging.Logger.Level: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.Array.ArrayType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Optype: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Value.Property: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.GAP: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.RevisionUtils.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.TechnicalInformation.Field: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.TechnicalInformation.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.InterquartileRange.ValueType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.GUIChooser.GUIChooserMenuPlugin.Menu: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.scripting.event.ScriptExecutionEvent.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.scripting.SyntaxDocument.ATTR_TYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.Run.SchemeType: Returns the enum constant of this type with the specified name.
valueReplacementsTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the tip text for this property
values() - Static method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.associations.NumericItem.Comparison: Returns an array containing the constants of this enum type, in the order they are declared.
Values - Class in weka.classifiers.trees.m5: Stores some statistics.
Values(int, int, int, Instances) - Constructor for class weka.classifiers.trees.m5.Values: Constructs an object which stores some statistics of the instances such as sum, squared sum, variance, standard deviation
values() - Static method in enum weka.core.Capabilities.Capability: Returns an array containing the constants of this enum type, in the order they are declared.
VALUES - Static variable in class weka.core.json.JSONInstances: the values attribute.
values() - Static method in enum weka.core.json.JSONNode.NodeType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.logging.Logger.Level: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.Array.ArrayType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Optype: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Value.Property: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.GAP: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.RevisionUtils.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.TechnicalInformation.Field: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.TechnicalInformation.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.filters.unsupervised.attribute.InterquartileRange.ValueType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.GUIChooser.GUIChooserMenuPlugin.Menu: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.scripting.event.ScriptExecutionEvent.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.scripting.SyntaxDocument.ATTR_TYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.Run.SchemeType: Returns an array containing the constants of this enum type, in the order they are declared.
valuesListTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
valueSparse(int) - Method in class weka.core.AbstractInstance: Returns an instance's attribute value in internal format, given an index in the sparse representation.
valueSparse(int) - Method in class weka.core.BinarySparseInstance: Returns an instance's attribute value in internal format.
valueSparse(int) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format, given an index in the sparse representation.
valueSparse(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseDouble(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseFloat(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseInt(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseString(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueString(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a String.
VARIABLE - Static variable in interface weka.core.mathematicalexpression.sym
variance(int) - Method in class weka.core.Instances: Computes the variance for a numeric attribute.
variance(Attribute) - Method in class weka.core.Instances: Computes the variance for a numeric attribute.
variance(double[]) - Static method in class weka.core.Utils: Computes the variance for an array of doubles.
varianceCoveredTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
varianceCoveredTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property.
VaryNode - Class in weka.classifiers.bayes.net: Part of ADTree implementation.
VaryNode(int) - Constructor for class weka.classifiers.bayes.net.VaryNode: Creates new VaryNode
VectorDictionary - Class in weka.core.pmml.jaxbbindings: Java class for VectorDictionary element declaration.
VectorDictionary() - Constructor for class weka.core.pmml.jaxbbindings.VectorDictionary
VectorDictionary - Class in weka.core.pmml: Class encapsulating the PMML VectorDictionary construct.
VectorDictionary(Element, MiningSchema) - Constructor for class weka.core.pmml.VectorDictionary: Constructor.
VectorFields - Class in weka.core.pmml.jaxbbindings: Java class for VectorFields element declaration.
VectorFields() - Constructor for class weka.core.pmml.jaxbbindings.VectorFields
VectorInstance - Class in weka.core.pmml.jaxbbindings: Java class for VectorInstance element declaration.
VectorInstance() - Constructor for class weka.core.pmml.jaxbbindings.VectorInstance
VectorInstance - Class in weka.core.pmml: Class encapsulating a PMML VectorInstance construct
VectorInstance(Array, List<FieldRef>) - Constructor for class weka.core.pmml.VectorInstance: Constructor
VectorInstance(Element, List<FieldRef>) - Constructor for class weka.core.pmml.VectorInstance: Constructor
VERBOSE - Static variable in class weka.core.ClassCache: whether to output some debug information.
VERBOSE - Static variable in class weka.core.ClassDiscovery: whether to output some debug information.
VERBOSE - Static variable in class weka.gui.GenericPropertiesCreator: whether to output some debug information
verboseTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
VerificationField - Class in weka.core.pmml.jaxbbindings: Java class for VerificationField element declaration.
VerificationField() - Constructor for class weka.core.pmml.jaxbbindings.VerificationField
VerificationFields - Class in weka.core.pmml.jaxbbindings: Java class for VerificationFields element declaration.
VerificationFields() - Constructor for class weka.core.pmml.jaxbbindings.VerificationFields
Version - Class in weka.core: This class contains the version number of the current WEKA release and some methods for comparing another version string.
Version() - Constructor for class weka.core.Version
VERSION - Static variable in class weka.core.Version: the complete version
VERSION_FILE - Static variable in class weka.core.Version: the version file
ViewerDialog - Class in weka.gui: A downsized version of the ArffViewer, displaying only one Instances-Object.
ViewerDialog(Frame) - Constructor for class weka.gui.ViewerDialog: initializes the dialog with the given parent
Visible - Interface in weka.gui.beans: Interface to something that has a visible (via BeanVisual) reprentation
VisualizableErrorEvent - Class in weka.gui.beans: Event encapsulating error information for a learning scheme that can be visualized in the DataVisualizer
VisualizableErrorEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.VisualizableErrorEvent
VisualizableErrorListener - Interface in weka.gui.beans: Interface to something that can accept VisualizableErrorEvents
VisualizePanel - Class in weka.gui.explorer: A slightly extended MatrixPanel for better support in the Explorer.
VisualizePanel() - Constructor for class weka.gui.explorer.VisualizePanel
VisualizePanel - Class in weka.gui.visualize: This panel allows the user to visualize a dataset (and if provided) a classifier's/clusterer's predictions in two dimensions.
VisualizePanel(VisualizePanelListener) - Constructor for class weka.gui.visualize.VisualizePanel: This constructor allows a VisualizePanelListener to be set.
VisualizePanel() - Constructor for class weka.gui.visualize.VisualizePanel: Constructor
VisualizePanelEvent - Class in weka.gui.visualize: This event Is fired to a listeners 'userDataEvent' function when The user on the VisualizePanel clicks submit.
VisualizePanelEvent(ArrayList<ArrayList<Double>>, Instances, Instances, int, int) - Constructor for class weka.gui.visualize.VisualizePanelEvent: This constructor creates the event with all the parameters set.
VisualizePanelListener - Interface in weka.gui.visualize: Interface implemented by a class that is interested in receiving submited shapes from a visualize panel.
VisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
VisualizeUtils - Class in weka.gui.visualize: This class contains utility routines for visualization
VisualizeUtils() - Constructor for class weka.gui.visualize.VisualizeUtils
VLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
Vote - Class in weka.classifiers.meta: Class for combining classifiers.
Vote() - Constructor for class weka.classifiers.meta.Vote
VotedPerceptron - Class in weka.classifiers.functions: Implementation of the voted perceptron algorithm by Freund and Schapire.
VotedPerceptron() - Constructor for class weka.classifiers.functions.VotedPerceptron
voteFlagTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property

W

waitUntilFinished() - Method in class weka.gui.beans.FlowRunner: Waits until all flows have finished executing before returning
WARNING - Static variable in class weka.core.Debug: the log level Warning
weight() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the weight assigned to this prediction.
weight() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the weight assigned to this prediction.
weight() - Method in interface weka.classifiers.evaluation.Prediction: Gets the weight assigned to this prediction.
weight(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Returns the weight a rule assigns to an instance.
weight() - Method in class weka.core.AbstractInstance: Returns the instance's weight.
weight() - Method in class weka.core.Attribute: Returns the attribute's weight.
weight() - Method in interface weka.core.Instance: Returns the instance's weight.
WEIGHT - Static variable in class weka.core.json.JSONInstances: the weight attribute.
WEIGHT_INVERSE - Static variable in class weka.classifiers.lazy.IBk: weight by 1/distance.
WEIGHT_NONE - Static variable in class weka.classifiers.lazy.IBk: no weighting.
WEIGHT_SIMILARITY - Static variable in class weka.classifiers.lazy.IBk: weight by 1-distance.
weightByDistanceTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
weightedAreaUnderPRC() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) AUPRC.
weightedAreaUnderPRC() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) AUPRC.
weightedAreaUnderROC() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) AUC.
weightedAreaUnderROC() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) AUC.
weightedFalseNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) false negative rate.
weightedFalseNegativeRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) false negative rate.
weightedFalsePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) false positive rate.
weightedFalsePositiveRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) false positive rate.
weightedFMeasure() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the macro weighted (by class size) average F-Measure.
weightedFMeasure() - Method in class weka.classifiers.Evaluation: Calculates the macro weighted (by class size) average F-Measure.
WeightedInstancesHandler - Interface in weka.core: Interface to something that makes use of the information provided by instance weights.
weightedMatthewsCorrelation() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) matthews correlation coefficient.
weightedMatthewsCorrelation() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) matthews correlation coefficient.
weightedPrecision() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) precision.
weightedPrecision() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) precision.
weightedRecall() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) recall.
weightedRecall() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) recall.
weightedTrueNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) true negative rate.
weightedTrueNegativeRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) true negative rate.
weightedTruePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) true positive rate.
weightedTruePositiveRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) true positive rate.
weightingKernelTipText() - Method in class weka.classifiers.lazy.LWL: Returns the tip text for this property.
WeightMass - Class in weka.classifiers.trees.ht: Simple container for a weight
WeightMass() - Constructor for class weka.classifiers.trees.ht.WeightMass
weights(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.C45Split: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NoSplit: Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
weightThresholdTipText() - Method in class weka.classifiers.meta.AdaBoostM1: Returns the tip text for this property
weightThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
weightTrimBetaTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
weightTrimBetaTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to get the weight value on a particular connection.
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to get the weight value on a particular connection.
weka - package weka
weka.associations - package weka.associations
weka.attributeSelection - package weka.attributeSelection
weka.classifiers - package weka.classifiers
weka.classifiers.bayes - package weka.classifiers.bayes
weka.classifiers.bayes.net - package weka.classifiers.bayes.net
weka.classifiers.bayes.net.estimate - package weka.classifiers.bayes.net.estimate
weka.classifiers.bayes.net.search - package weka.classifiers.bayes.net.search
weka.classifiers.bayes.net.search.ci - package weka.classifiers.bayes.net.search.ci
weka.classifiers.bayes.net.search.fixed - package weka.classifiers.bayes.net.search.fixed
weka.classifiers.bayes.net.search.global - package weka.classifiers.bayes.net.search.global
weka.classifiers.bayes.net.search.local - package weka.classifiers.bayes.net.search.local
weka.classifiers.evaluation - package weka.classifiers.evaluation
weka.classifiers.evaluation.output.prediction - package weka.classifiers.evaluation.output.prediction
weka.classifiers.functions - package weka.classifiers.functions
weka.classifiers.functions.neural - package weka.classifiers.functions.neural
weka.classifiers.functions.supportVector - package weka.classifiers.functions.supportVector
weka.classifiers.lazy - package weka.classifiers.lazy
weka.classifiers.lazy.kstar - package weka.classifiers.lazy.kstar
weka.classifiers.meta - package weka.classifiers.meta
weka.classifiers.misc - package weka.classifiers.misc
weka.classifiers.pmml.consumer - package weka.classifiers.pmml.consumer
weka.classifiers.pmml.producer - package weka.classifiers.pmml.producer
weka.classifiers.rules - package weka.classifiers.rules
weka.classifiers.rules.part - package weka.classifiers.rules.part
weka.classifiers.trees - package weka.classifiers.trees
weka.classifiers.trees.ht - package weka.classifiers.trees.ht
weka.classifiers.trees.j48 - package weka.classifiers.trees.j48
weka.classifiers.trees.lmt - package weka.classifiers.trees.lmt
weka.classifiers.trees.m5 - package weka.classifiers.trees.m5
weka.classifiers.xml - package weka.classifiers.xml
weka.clusterers - package weka.clusterers
weka.core - package weka.core
weka.core.converters - package weka.core.converters
weka.core.json - package weka.core.json
weka.core.logging - package weka.core.logging
weka.core.mathematicalexpression - package weka.core.mathematicalexpression
weka.core.matrix - package weka.core.matrix
weka.core.neighboursearch - package weka.core.neighboursearch
weka.core.neighboursearch.balltrees - package weka.core.neighboursearch.balltrees
weka.core.neighboursearch.covertrees - package weka.core.neighboursearch.covertrees
weka.core.neighboursearch.kdtrees - package weka.core.neighboursearch.kdtrees
weka.core.pmml - package weka.core.pmml
weka.core.pmml.jaxbbindings - package weka.core.pmml.jaxbbindings
weka.core.scripting - package weka.core.scripting
weka.core.stemmers - package weka.core.stemmers
weka.core.tokenizers - package weka.core.tokenizers
weka.core.xml - package weka.core.xml
weka.datagenerators - package weka.datagenerators
weka.datagenerators.classifiers.classification - package weka.datagenerators.classifiers.classification
weka.datagenerators.classifiers.regression - package weka.datagenerators.classifiers.regression
weka.datagenerators.clusterers - package weka.datagenerators.clusterers
weka.estimators - package weka.estimators
weka.experiment - package weka.experiment
weka.experiment.xml - package weka.experiment.xml
weka.filters - package weka.filters
weka.filters.supervised.attribute - package weka.filters.supervised.attribute
weka.filters.supervised.instance - package weka.filters.supervised.instance
weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute
weka.filters.unsupervised.instance - package weka.filters.unsupervised.instance
weka.filters.unsupervised.instance.subsetbyexpression - package weka.filters.unsupervised.instance.subsetbyexpression
weka.gui - package weka.gui
weka.gui.arffviewer - package weka.gui.arffviewer
weka.gui.beans - package weka.gui.beans
weka.gui.beans.xml - package weka.gui.beans.xml
weka.gui.boundaryvisualizer - package weka.gui.boundaryvisualizer
weka.gui.experiment - package weka.gui.experiment
weka.gui.explorer - package weka.gui.explorer
weka.gui.filters - package weka.gui.filters
weka.gui.graphvisualizer - package weka.gui.graphvisualizer
weka.gui.hierarchyvisualizer - package weka.gui.hierarchyvisualizer
weka.gui.scripting - package weka.gui.scripting
weka.gui.scripting.event - package weka.gui.scripting.event
weka.gui.sql - package weka.gui.sql
weka.gui.sql.event - package weka.gui.sql.event
weka.gui.streams - package weka.gui.streams
weka.gui.treevisualizer - package weka.gui.treevisualizer
weka.gui.visualize - package weka.gui.visualize
weka.gui.visualize.plugins - package weka.gui.visualize.plugins
WEKA_HOME - Static variable in class weka.core.WekaPackageManager: Default path to where Weka's configuration and packages are stored
WekaEnumeration<E> - Class in weka.core: Class for enumerating an array list's elements.
WekaEnumeration(List<E>) - Constructor for class weka.core.WekaEnumeration: Constructs an enumeration.
WekaEnumeration(List<E>, int) - Constructor for class weka.core.WekaEnumeration: Constructs an enumeration with a special element.
WekaException - Exception in weka.core: Class for Weka-specific exceptions.
WekaException() - Constructor for exception weka.core.WekaException: Creates a new WekaException with no message.
WekaException(String) - Constructor for exception weka.core.WekaException: Creates a new WekaException.
WekaOffscreenChartRenderer - Class in weka.gui.beans: Default OffscreenChartRenderer that uses Weka's built-in chart and graph classes.
WekaOffscreenChartRenderer() - Constructor for class weka.gui.beans.WekaOffscreenChartRenderer
WekaPackageManager - Class in weka.core: Class providing package management and manipulation routines.
WekaPackageManager() - Constructor for class weka.core.WekaPackageManager
wekaStaticWrapper(Sourcable, String) - Static method in class weka.classifiers.evaluation.Evaluation: Wraps a static classifier in enough source to test using the weka class libraries.
wekaStaticWrapper(Sourcable, String) - Static method in class weka.classifiers.Evaluation: Wraps a static classifier in enough source to test using the weka class libraries.
wekaStaticWrapper(Sourcable, String, Instances, Instances) - Static method in class weka.filters.Filter: generates source code from the filter
WekaTaskMonitor - Class in weka.gui: This panel records the number of weka tasks running and displays a simple bird animation while their are active tasks
WekaTaskMonitor() - Constructor for class weka.gui.WekaTaskMonitor: Constructor
WekaWrapper - Interface in weka.gui.beans: Interface to something that can wrap around a class of Weka algorithms (classifiers, filters etc).
WEST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.C45Split: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NoSplit: Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit
width() - Method in class weka.core.matrix.ExponentialFormat
width() - Method in class weka.core.matrix.FlexibleDecimalFormat
width() - Method in class weka.core.matrix.FloatingPointFormat
WIDTH - Static variable in class weka.core.neighboursearch.KDTree: The index of WIDTH (MAX-MIN) value in attributes' range array.
WIDTH - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of width value (max-min) in an array of attributes' range.
WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: default width
WIDTH - Static variable in class weka.gui.sql.SqlViewer: the width property in the history file.
WIN_STRING - Variable in class weka.experiment.ResultMatrix: win string.
windowActivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is activated
windowClosed(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is closed
windowClosing(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is in the process of closing
windowDeactivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is deactivated
windowDeiconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is deiconified
windowIconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is iconified
windowListChanged() - Method in class weka.gui.Main: is called when window list changed somehow (add or remove).
windowOpened(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is has been opened
windowSizeTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
WITHIN_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent
wordsToKeepTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
WordTokenizer - Class in weka.core.tokenizers: A simple tokenizer that is using the java.util.StringTokenizer class to tokenize the strings.
WordTokenizer() - Constructor for class weka.core.tokenizers.WordTokenizer
WrapperSubsetEval - Class in weka.attributeSelection: WrapperSubsetEval:

Evaluates attribute sets by using a learning scheme.
WrapperSubsetEval() - Constructor for class weka.attributeSelection.WrapperSubsetEval: Constructor.
write(Writer) - Method in class weka.classifiers.CostMatrix: Writes out a matrix.
write(Instances) - Method in class weka.core.converters.ConverterUtils.DataSink: writes the given data either via the saver or to the defined output stream (depending on the constructor).
write(String, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data to the given file.
write(Saver, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data via the given saver.
write(OutputStream, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data to the given stream (always in ARFF format).
write(Writer) - Method in class weka.core.matrix.Matrix: Writes out a matrix.
write(Writer) - Method in class weka.core.Matrix: Deprecated. Writes out a matrix.
write(String, Object) - Static method in class weka.core.SerializationHelper: serializes the given object to the specified file.
write(OutputStream, Object) - Static method in class weka.core.SerializationHelper: serializes the given object to the specified stream.
write(String) - Method in class weka.core.Stopwords: Writes the current stopwords to the given file
write(File) - Method in class weka.core.Stopwords: Writes the current stopwords to the given file
write(BufferedWriter) - Method in class weka.core.Stopwords: Writes the current stopwords to the given writer.
write(byte[], int, int) - Method in class weka.core.Tee: Writes len bytes from the specified byte array starting at offset off to this stream.
write(int) - Method in class weka.core.Tee: Writes the specified byte to this stream.
write(String, Object) - Static method in class weka.core.xml.KOML: writes the XML-serialized object to the given file
write(File, Object) - Static method in class weka.core.xml.KOML: write the XML-serialized object to the given file
write(OutputStream, Object) - Static method in class weka.core.xml.KOML: writes the XML-serialized object to a stream
write(String) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given file.
write(File) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given file.
write(OutputStream) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given stream.
write(Writer) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given writer.
write(String, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the file
write(File, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the file
write(OutputStream, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the stream
write(Writer, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the writer
write() - Method in class weka.core.xml.XMLSerializationMethodHandler: returns the handler for write methods
write(String, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given file
write(File, Object) - Static method in class weka.core.xml.XStream: write the XML-serialized object to the given file
write(OutputStream, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given output stream
write(Writer, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given Writer.
write(String, Experiment) - Static method in class weka.experiment.Experiment: Writes the experiment to disk.
writeAll(String, Object[]) - Static method in class weka.core.SerializationHelper: serializes the given objects to the specified file.
writeAll(OutputStream, Object[]) - Static method in class weka.core.SerializationHelper: serializes the given objects to the specified stream.
writeBatch() - Method in class weka.core.converters.AbstractSaver: Writes to a file in batch mode To be overridden.
writeBatch() - Method in class weka.core.converters.ArffSaver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.C45Saver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.CSVSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.DatabaseSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.JSONSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.LibSVMSaver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.MatlabSaver: Writes a Batch of instances.
writeBatch() - Method in interface weka.core.converters.Saver: Writes to a destination in batch mode
writeBatch() - Method in class weka.core.converters.SerializedInstancesSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.SVMLightSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.XRFFSaver: Writes a Batch of instances
writeBeanConnection(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanConncetion to a DOM structure.
writeBeanInstance(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanInstance to a DOM structure.
writeBeanLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Loader (a bean) to a DOM structure.
writeBeanSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Saver (a bean) to a DOM structure.
writeBeanVisual(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanVisual to a DOM structure.
writeCollection(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Collection to a DOM structure.
writeColor(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Color to a DOM structure.
writeColorUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given ColorUIResource to a DOM structure.
writeCostMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given CostMatrix (old) to a DOM structure.
writeCurve(String, Estimator, double, double, int) - Static method in class weka.estimators.EstimatorUtils: Output of an n points of a density curve.
writeCurve(String, Estimator, Estimator, double, double, double, int) - Static method in class weka.estimators.EstimatorUtils: Output of an n points of a density curve.
writeDefaultListModel(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given DefaultListModel to a DOM structure.
writeDimension(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Dimension to a DOM structure.
writeDOT(String, String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Static method in class weka.gui.graphvisualizer.DotParser: This method saves a graph in a file in DOT format.
writeFont(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Font to a DOM structure.
writeFontUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given FontUIResource to a DOM structure.
writeIncremental(Instance) - Method in class weka.core.converters.AbstractSaver: Method for incremental saving.
writeIncremental(Instance) - Method in class weka.core.converters.ArffSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.C45Saver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.CSVSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.DatabaseSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.LibSVMSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.MatlabSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in interface weka.core.converters.Saver: Writes to a destination in incremental mode.
writeIncremental(Instance) - Method in class weka.core.converters.SVMLightSaver: Saves an instances incrementally.
writeLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Loader to a DOM structure.
writeMap(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Map to a DOM structure.
writeMatrix(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Matrix to a DOM structure.
writeMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Matrix (old) to a DOM structure.
writeMetaBean(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given MetaBean to a DOM structure.
writePoint(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Point to a DOM structure.
writePropertyNode(Element, Object, String) - Method in class weka.experiment.xml.XMLExperiment: adds the given PropertyNode to a DOM structure.
writeSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Saver to a DOM structure.
writeToFile(String, Object) - Static method in class weka.core.Debug: Writes the given object to the specified file.
writeToFile(String, String) - Static method in class weka.core.Debug: Writes the given message to the specified file.
writeToFile(String, Object, boolean) - Static method in class weka.core.Debug: Writes the given object to the specified file.
writeToFile(String, String, boolean) - Static method in class weka.core.Debug: Writes the given message to the specified file.
writeToXML(Element, Object, String) - Method in class weka.core.xml.XMLSerialization: adds the given Object to a DOM structure.
writeXMLBIF03(String, String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Static method in class weka.gui.graphvisualizer.BIFParser: This method writes a graph in XMLBIF ver.

X

x - Variable in class weka.gui.graphvisualizer.GraphNode

The x and y position of the node

X_SHAPE - Static variable in class weka.gui.visualize.Plot2D

XCoordinates - Class in weka.core.pmml.jaxbbindings

Java class for XCoordinates element declaration.

XCoordinates() - Constructor for class weka.core.pmml.jaxbbindings.XCoordinates

xLabelFreqTipText() - Method in class weka.gui.beans.StripChart

GUI Tip text

xlogx(int) - Static method in class weka.core.Utils

Returns c*log2(c) for a given integer value c.

XML - Class in weka.classifiers.evaluation.output.prediction

Outputs the predictions in XML.

The following DTD is used:

<!DOCTYPE predictions
[
<!ELEMENT predictions (prediction*)>
<!ATTLIST predictions version CDATA "3.5.8">
<!ATTLIST predictions name CDATA #REQUIRED>

<!ELEMENT prediction ((actual_label,predicted_label,error,(prediction|distribution),attributes?)|(actual_value,predicted_value,error,attributes?))>
<!ATTLIST prediction index CDATA #REQUIRED>

<!ELEMENT actual_label ANY>
<!ATTLIST actual_label index CDATA #REQUIRED>
<!ELEMENT predicted_label ANY>
<!ATTLIST predicted_label index CDATA #REQUIRED>
<!ELEMENT error ANY>
<!ELEMENT prediction ANY>
<!ELEMENT distribution (class_label+)>
<!ELEMENT class_label ANY>
<!ATTLIST class_label index CDATA #REQUIRED>
<!ATTLIST class_label predicted (yes|no) "no">
<!ELEMENT actual_value ANY>
<!ELEMENT predicted_value ANY>
<!ELEMENT attributes (attribute+)>
<!ELEMENT attribute ANY>
<!ATTLIST attribute index CDATA #REQUIRED>
<!ATTLIST attribute name CDATA #REQUIRED>
<!ATTLIST attribute type (numeric|date|nominal|string|relational) #REQUIRED>
]
>

Valid options are:

XML() - Constructor for class weka.classifiers.evaluation.output.prediction.XML

XMLBasicSerialization - Class in weka.core.xml

This serializer contains some read/write methods for common classes that are not beans-conform.

XMLBasicSerialization() - Constructor for class weka.core.xml.XMLBasicSerialization

initializes the serialization

XMLBeans - Class in weka.gui.beans.xml

This class serializes and deserializes a KnowledgeFlow setup to and fro XML.

XMLBeans(JComponent, BeanContextSupport, int) - Constructor for class weka.gui.beans.xml.XMLBeans

initializes the serialization for layouts

XMLBeans(JComponent, BeanContextSupport, int, int) - Constructor for class weka.gui.beans.xml.XMLBeans

initializes the serialization for different types of data

XMLClassifier - Class in weka.classifiers.xml

This class serializes and deserializes a Classifier instance to and fro XML.

XMLClassifier() - Constructor for class weka.classifiers.xml.XMLClassifier

initializes the serialization

XMLDocument - Class in weka.core.xml

This class offers some methods for generating, reading and writing XML documents.
It can only handle UTF-8.

XMLDocument() - Constructor for class weka.core.xml.XMLDocument

initializes the factory with non-validating parser.

XMLDocument(String) - Constructor for class weka.core.xml.XMLDocument

Creates a new instance of XMLDocument.

XMLDocument(File) - Constructor for class weka.core.xml.XMLDocument

Creates a new instance of XMLDocument.

XMLDocument(InputStream) - Constructor for class weka.core.xml.XMLDocument

Creates a new instance of XMLDocument.

XMLDocument(Reader) - Constructor for class weka.core.xml.XMLDocument

Creates a new instance of XMLDocument.

XMLExperiment - Class in weka.experiment.xml

This class serializes and deserializes an Experiment instance to and fro XML.
It omits the options from the Experiment, since these are handled by the get/set-methods.

XMLExperiment() - Constructor for class weka.experiment.xml.XMLExperiment

initializes the serialization

XMLInstances - Class in weka.core.xml

XML representation of the Instances class.

XMLInstances() - Constructor for class weka.core.xml.XMLInstances

the default constructor

XMLInstances(Instances) - Constructor for class weka.core.xml.XMLInstances

generates the XML structure based on the given data

XMLInstances(Reader) - Constructor for class weka.core.xml.XMLInstances

generates the Instances directly from the reader containing the XML data.

XMLOptions - Class in weka.core.xml

A class for transforming options listed in XML to a regular WEKA command line string.

XMLOptions() - Constructor for class weka.core.xml.XMLOptions

Creates a new instance of XMLOptions.

XMLOptions(String) - Constructor for class weka.core.xml.XMLOptions

Creates a new instance of XMLOptions.

XMLOptions(File) - Constructor for class weka.core.xml.XMLOptions

Creates a new instance of XMLOptions.

XMLOptions(InputStream) - Constructor for class weka.core.xml.XMLOptions

Creates a new instance of XMLOptions.

XMLOptions(Reader) - Constructor for class weka.core.xml.XMLOptions

Creates a new instance of XMLOptions.

XMLSerialization - Class in weka.core.xml

With this class objects can be serialized to XML instead into a binary format.

XMLSerialization() - Constructor for class weka.core.xml.XMLSerialization

initializes the serialization

XMLSerializationMethodHandler - Class in weka.core.xml

This class handles relationships between display names of properties (or classes) and Methods that are associated with them.

XMLSerializationMethodHandler(Object) - Constructor for class weka.core.xml.XMLSerializationMethodHandler

initializes the method handling, executes also clear(), which adds initial methods automatically.

XRFFLoader - Class in weka.core.converters

Reads a source that is in the XML version of the ARFF format.

XRFFLoader() - Constructor for class weka.core.converters.XRFFLoader

XRFFSaver - Class in weka.core.converters

Writes to a destination that is in the XML version of the ARFF format.

XRFFSaver() - Constructor for class weka.core.converters.XRFFSaver

Constructor

xStats - Variable in class weka.experiment.PairedStats

The stats associated with the data in column 1

XStream - Class in weka.core.xml

This class is a helper class for XML serialization using XStream .

XStream() - Constructor for class weka.core.xml.XStream

XSTREAM - Static variable in class weka.gui.beans.SerializedModelSaver

xySum - Variable in class weka.experiment.PairedStats

The sum of the products

Y

y - Variable in class weka.gui.graphvisualizer.GraphNode: The x and y position of the node
YCoordinates - Class in weka.core.pmml.jaxbbindings: Java class for YCoordinates element declaration.
YCoordinates() - Constructor for class weka.core.pmml.jaxbbindings.YCoordinates
YongSplitInfo - Class in weka.classifiers.trees.m5: Stores split information.
YongSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.YongSplitInfo: Constructs an object which contains the split information
yStats - Variable in class weka.experiment.PairedStats: The stats associated with the data in column 2
yybegin(int) - Method in class weka.core.json.Scanner: Enters a new lexical state
yybegin(int) - Method in class weka.core.mathematicalexpression.Scanner: Enters a new lexical state
yybegin(int) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Enters a new lexical state
yycharat(int) - Method in class weka.core.json.Scanner: Returns the character at position pos from the matched text.
yycharat(int) - Method in class weka.core.mathematicalexpression.Scanner: Returns the character at position pos from the matched text.
yycharat(int) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Returns the character at position pos from the matched text.
yyclose() - Method in class weka.core.json.Scanner: Closes the input stream.
yyclose() - Method in class weka.core.mathematicalexpression.Scanner: Closes the input stream.
yyclose() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Closes the input stream.
YYEOF - Static variable in class weka.core.json.Scanner: This character denotes the end of file
YYEOF - Static variable in class weka.core.mathematicalexpression.Scanner: This character denotes the end of file
YYEOF - Static variable in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: This character denotes the end of file
YYINITIAL - Static variable in class weka.core.json.Scanner
YYINITIAL - Static variable in class weka.core.mathematicalexpression.Scanner: lexical states
YYINITIAL - Static variable in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner
yylength() - Method in class weka.core.json.Scanner: Returns the length of the matched text region.
yylength() - Method in class weka.core.mathematicalexpression.Scanner: Returns the length of the matched text region.
yylength() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Returns the length of the matched text region.
yypushback(int) - Method in class weka.core.json.Scanner: Pushes the specified amount of characters back into the input stream.
yypushback(int) - Method in class weka.core.mathematicalexpression.Scanner: Pushes the specified amount of characters back into the input stream.
yypushback(int) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Pushes the specified amount of characters back into the input stream.
yyreset(Reader) - Method in class weka.core.json.Scanner: Resets the scanner to read from a new input stream.
yyreset(Reader) - Method in class weka.core.mathematicalexpression.Scanner: Resets the scanner to read from a new input stream.
yyreset(Reader) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Resets the scanner to read from a new input stream.
yystate() - Method in class weka.core.json.Scanner: Returns the current lexical state.
yystate() - Method in class weka.core.mathematicalexpression.Scanner: Returns the current lexical state.
yystate() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Returns the current lexical state.
yytext() - Method in class weka.core.json.Scanner: Returns the text matched by the current regular expression.
yytext() - Method in class weka.core.mathematicalexpression.Scanner: Returns the text matched by the current regular expression.
yytext() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Scanner: Returns the text matched by the current regular expression.

Z

ZeroR - Class in weka.classifiers.rules: Class for building and using a 0-R classifier.
ZeroR() - Constructor for class weka.classifiers.rules.ZeroR
zipit(String, String) - Method in class weka.experiment.OutputZipper: Saves a string to either an individual gzipped file or as an entry in a zip file.
ZMaxTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property

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